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Abstract: Material requirements planning (MRP) systems became a prominent approach to managing the flow of raw material and components on the factory floor in the late 20th century. Its adoption was not an over night phenomenon, but was a slow progression over many decades. This article chronicles many developments and events during the formative years of MRP, highlighting changes in computer technology and contributions by key early proponents of this approach for managing the flow of material on the factory floor. [Copyright &y& Elsevier]

Abstract: This study empirically tests the rigid flexibility model proposed by Collins and Schmenner [Collins, R.S., Schmenner, R.W., 1993. Achieving rigid flexibility: factory focus for the 1990s. European Management Journal 11 (4), 443–447]. It investigates relationships between flexibility performance and adoption of simplicity and discipline programs in manufacturing. The research replicates the study by Collins et al. [Collins, R.S., Cordon, C., Julien, D., 1998. An empirical test of the rigid flexibility model. Journal of Operations Management 16 (2–3), 133–146] with some modifications, including the use of a broader international database, the assessment of both technology and organizational programs, and the testing of the moderating role of dedicated line layout on the relationships between simplicity, discipline and flexibility. Analysis of data from 285 manufacturers of fabricated metal products, machinery, and equipment from 14 countries indicates that simplicity and discipline related positively to performance in product customization, volume flexibility, mix flexibility, and time to market, and that some of these relationships were more positive in high volume processes than in low volume processes. The results provide empirical validation to the rigid flexibility model in an international manufacturing context. [Copyright &y& Elsevier]

Abstract: The complexity of planning tasks have increased over the past decade. There is relatively poor understanding what the implications are of increased task complexity in planning and scheduling operations. Previous work in the behavioral sciences have investigated the concept of cognitive load, addressing both task complexity and task workload or stress, and have concluded that decision makers tend to resort to routine action and reduce the variety in their actions with increasing complexity and workload. Alternatively, control theory suggests that a higher variety of actions is needed to deal with more complex problems. In this paper, we investigate the effects of task complexity in a chemical plant on the variety of actions deployed by the planners. The single work center resource structure and the availability of actual planning data from an MRP-application database allows us to both use field data and study a situation which is simple enough to measure the main effect. Our results suggest that increased task complexity without time pressure does indeed lead to increased action variety deployed by the planners. [Copyright &y& Elsevier]

This paper investigates the impact of between- and within-product parts commonality on the workload of a manufacturing firm using an MRP system. More specifically, we investigate the impact of several operational factors and their interactions with part commonality. We develop and validate a large simulation of an MRP system and integrate the generation of planned order releases with workload estimation on the shop floor. The results indicate that increasing parts commonality has positive effects in terms of average shop load but does lead to greater variability in terms of loadings as well as increasing system disruption. Further, we also find that the number of work centers significantly impacts the shop floor effects of commonality. Hence, although an increase in parts commonality results in less design effort and increased standardization, the negative effects of increasing commonality often appear on the shop floor level. This points to a need for the effective management of parts commonality by assessing the tradeoff between strategic "benefits" and operational "costs". [ABSTRACT FROM AUTHOR]

Schedule nervousness caused by uncertainty in demand or supply or by dynamic lot-sizing can be an obstacle to effective execution of material requirements planning (MRP) systems. Previous studies on the effectiveness of alternative approaches for dampening nervousness almost always considered single-level product structures and deterministic demand conditions. This study evaluates the effectiveness of three strategies for reducing nervousness in multi-level MRP systems under demand uncertainty: (1) freezing, (2) end-item safety stock, and (3) lot-for-lot scheduling below level 0. The strategies are evaluated under a wide range of operating conditions characterized by variations in item cost structure, product structure, demand uncertainty, and lot-sizing methods used. A multi-level MRP system is simulated to study the relative performance of the three strategies. Results indicate that freezing the master production schedule is the most effective approach in terms of reducing both instability and cost as the freeze length covers the cumulative lead time. It is also the least sensitive to changes in operating conditions. [ABSTRACT FROM AUTHOR]

Responding to regional and international competition, many manufacturing companies have adopted MRP systems to improve their manufacturing operations. Of primary interest to managers and users of MRP is the benefits that can be derived from using the MRP technology. While the literature abounds with MRP implementation studies, there is a dearth of research that examines the determinants of specific MRP benefits. Knowledge of the determinants would enable MRP managers and users to concentrate on key areas to achieve benefits that match their company goals. This paper identifies the organizational, implementational, and technological variables that affect specific MRP benefits as reported by Singapore manufacturing companies in the most extensive MRP survey ever conducted in Singapore. Using Alternating Conditional Expectation (ACE), an advanced statistical modeling technique that increases the model fit by approximating the optimal transformations for the dependent and independent variables, the regression models developed reveal more accurate relationships compared to those in previous MRP studies. Our findings offer several novel and valuable insights into the MRP benefit-determinant relationship. The major finding is that determinant variables such as data accuracy, people support, degree of integration, and company size affect benefits in a nonlinear fashion. Data accuracy was found to be critical in affecting operational efficiency, customer service, and interdepartmental coordination benefits. Another finding suggests that when people support and data accuracy degenerate to a critical level, users might still derive increased benefits by resorting to secondary sources to accomplish their work. Users should strive for a high degree of integration to achieve full operational efficiency and coordination benefits. Partial integration does not appear to provide significant improvements. We also found that increasing company size has a positive, followed by a negative impact on operational efficiency. Lastly, our findings suggest that the pattern of technical complaints can be an indicator of system usage and interdepartmental coordination. Our findings have important implications for managers and users of MRP. [ABSTRACT FROM AUTHOR]

This study investigates the impact of using material flow control and order release throttling mechanisms on shop floor effectiveness in MRP based order release environments. The research methodology involves simulation experiments conducted using a flow shop model of a manufacturing and assembly setting. Specifically addressed issue is the decoupling of shop floor control decisions from MRP release schedules. This decoupling effect is implemented through the use of smaller production batch sizes, staggering the release of the production quantities to initial work stations, and using transfer batches. In a 14 parts /9 processes simulation environment, the effects of shop floor control decisions are evaluated based on average hours of work in process inventory and average number of tardy units for the simulated planning horizon. Experimental results suggest that increasing material flow frequency through smaller process and transfer batch sizes have significant consequences on inventory and service levels. By separating work in process inventories into two components, it is shown that reducing batch sizes may not affect inventory levels of asynchronized assembly units (i.e. component delay). The results also indicate the presence of a possible threshold effect for throttling and staggering work order releases where service levels are compromised and marginal gain on inventory reduction diminishes. [ABSTRACT FROM AUTHOR]

Freezing the master production schedule (MPS) is one of the commonly used methods to reduce schedule instability or nervousness in material requirements planning (MRP) systems. However, the impact of MPS freezing parameters in multilevel MRP systems has not been fully understood. This paper investigates the impact of MPS freezing parameters on the total cost, schedule instability and service levels in multilevel MRP systems under demand uncertainty conditions. The MPS freezing parameters included in this study are: (1) planning horizons; (2) freezing proportions; (3) freezing methods; and (4) replanning periodicity. The paper also examines the impact of forecasting errors on the selection of MPS freezing parameters and system performance. A model was built to simulate forecasting, master production scheduling and material requirements planning operations in a manufacturing company. The company is assumed to produce two end items with no component commonality. The company operates in a make-to-stock environment. No back orders are allowed and thus any shortage will become a loss of sales. Through a comprehensive simulation experiment and statistical analysis, the study arrived at the following findings: (1) Forecasting errors significantly increase total costs and schedule instability, and reduce the service level in multilevel MRP systems. The selection of forecasting models has a significant impact on system performance. In addition, forecasting errors also influence the selection of some MPS freezing parameters. (2) A planning horizon of four natural ordering cycles results in a lower total cost and schedule instability and a higher service level than a planning horizon of eight natural ordering cycles under demand uncertainty condition, but a higher total cost and schedule instability under deterministic demand conditions. Thus the prolongation of the planning horizon can actually worsen MRP performance under demand uncertainty conditions while it improves MRP performance under deterministic demand conditions. (3) A higher freezing proportion results in a lower total cost and schedule instability, and does not influence the service level under deterministic demand conditions. Therefore, freezing the entire planning horizon is the best option in this case. However, a higher freezing proportion often results in a higher cost, and a lower service level, while reducing schedule instability under demand uncertainty conditions. As a result, the choice of freezing proportion should be based on the required trade-offs among the three performance criteria under demand uncertainty conditions. (4) The order-based freezing method results in lower total costs than the period-based method in most cases. In terms of schedule instability, the period-based method with freezing proportion of 1.0 performs the best. In terms of service level, the period-based method with freezing proportion of 1.0 performs the worst; the period-based method with freezing proportion of 0.25 performs the best. The selection of the freezing method should be considered in combination with the freezing proportion to achieve the required trade-offs among the performance criteria of total costs, schedule instability, and service level. (5) A higher replanning periodicity results in a lower total cost, schedule instability, and a higher service level under both deterministic and stochastic demand conditions. Thus, less frequent replanning improves system performance. These conclusions may help MRP practitioners to select MPS freezing parameters in multilevel MRP systems. [ABSTRACT FROM AUTHOR]

Results are presented of a simulation analysis of a hypothetical fabrication and assembly shop controlled by material requirements planning. The purpose of the study is to investigate the impact of lot sizing on the customer service performance of dispatching techniques in an MRP-controlled assembly job shop operating near capacity. Six dispatching techniques are compared based on the tardiness of customer orders under four lot-sizing techniques, two levels of demand, and two levels of nervousness. The study is conducted with a stable product mix, limited production capacity, and fixed routings. Random shifts in short-term product mix cause short-term bottlenecks, but one of the 15 work stations has less than 10% idle time and is the most commonly encountered bottleneck. The interaction of lot-sizing and dispatching techniques was found to be a function of capacity utilization, a factor influenced by demand and nervousness level. Under low demand, earliest job due date yielded the best performance with regard to the percentage of tardy orders, average order tardiness, and maximum order tardiness. Under high demand, earliest job due date performed best with respect to average order tardiness and maximum order tardiness, but the best dispatching technique with respect to percentage of tardy orders depended on the lot-sizing technique and the nervousness level. Under high demand and high nervousness, effective capacity decreased and queues increased with economic order quantity, period order quantity, or least total cost. Economic order quantity generated the smallest batches. Period order quantity and least total cost generated extra set-ups under high nervousness. Use of either of the three lot-sizing techniques at high demand and high nervousness forced a choice between a dispatching technique that yields a low percentage of orders tardy (earliest modified operation due date) and one that generates low maximum order tardiness (earliest job due date). The Silver-Meal heuristic consumed less effective capacity than the other lot-sizing techniques. Using Silver-Meal at high demand and nervousness, earliest job due date performed best with respect to each tardiness measure. The bottleneck causes the plant to behave like a single machine shop. Since large queues are maintained at the bottleneck, that is where the choice of dispatching technique is critical. Earliest due date minimizes the percentage of tardy orders. Earliest modified operation due date, operating like the shortest processing time rule, minimizes the percentage of tardy orders, but maximum tardiness is high. These results may stimulate new interest in single-machine scheduling. The combination of least total cost and earliest job due produced the best overall performance at low demand. At high demand, Silver-Meal and earliest job due date achieved the best performance. [ABSTRACT FROM AUTHOR]

This paper deals with MRP treatments of the coexistence of MRP and kanban systems. In practical applications, MRP and kanban can both exist in a factory. When a production system contains parts managed by an MRP system and parts managed by a kanban system, MRP needs to have a special way of dealing with those parts managed by the kanban system in order to provide accurate gross demand data for the MRP system. A modified MRP for treating parts ordered through kanbans with the coexistence of MRP and kanbans is proposed. Along with two other existing methods (one by Karmarkar and another by a major tractor company), three methods are compared in a GPSS simulation study. Empirical results regarding inventory and shortages from the simulation study showed that both the proposed modified MRP and Karmarkar's methods of dealing with parts ordered by kanbans performed quite well. This research study suggests two effective lot-sizing rules to be used in MRP part explosion for kanban-controlled stages of a production system in which some stages are controlled by kanbans and other stages by MRP releases. The simulation study established empirical evidence for the effectiveness of these two lot sizing rules. [ABSTRACT FROM AUTHOR]

This work presents an exploratory empirical study of the process of formulating and implementing manufacturing strategy within the framework of overall corporate strategy, as practiced by a crosssectional representation of leading-edge firms. A conference was held where executives representing six firms in the following industries—computer equipment, pharmaceuticals, valves, telecommunications, furniture, and electrical submersible pumps— described the process of manufacturing strategy formulation and implementation as practiced within their firms. Although the firms represented a diversity in terms of sales volume, longevity, and geographic location, they shared several commonalities including Class A use of MRP, excellent customer service records, and maintenance of accurate manufacturing data bases. In addition, despite increasingly competitive conditions within their respective industries, none of the firms considered itself to be the low cost producer in the industry. Competitive strength was sustained through innovation, quality, and service. The process of strategy formulation varied among the firms in terms of participants, complexity, and degree of formalization. Several findings emerged from the conference. First, all firms followed a traditional hierarchical topdown approach in formulating manufacturing strategy under the umbrella of corporate strategy. In general, the process was reactive to corporate strategy although the executives reported greater involvement on the part of manufacturing in corporate strategic planning through the identification of competitive strengths and weaknesses. Manufacturing strategy was also viewed as reactive to marketing strategy with marketing playing the role of boundary spanner in assessing competitors and customers to support the manufacturing strategy effort. Finally, some of the executives stated that several of the traditional manufacturing resource decision categories were constrained by corporate philosophy. Examples of constraining policies included facilities, capacity, vertical integration, and organization. On the other hand, all the firms were able to develop strategies for process choice/technology, quality, manufacturing planning and control, and people. The executives described the implementation process as one of gaining employee acceptance of the strategy through lower level involvement and teamwork. Although communication was a major concern in implementing the strategy, the executives all stated that the most difficult task was changing corporate culture, which was often entrenched in obsolete cost accounting systems, to make it supportive of the new strategy. Other problems confronted by the firms included maintaining consistency among managers across all levels in the organization, gaining top management support, and developing appropriate styles of leadership. The study shows that these firms' processes of formulating manufacturing strategy seem to follow the general conceptual models developed in the academic literature. However, the executives indicated that the real benefits of strategy come from implementation, which is a less structured and behaviorally oriented process. Future research must address infrastructural issues including culture, performance measurement, and managerial style. [ABSTRACT FROM AUTHOR]

As material requirements planning systems do not consider capacity limitations in their inherent logic, considerable effort must be spent to achieve feasible production plans. This simulation study examines the cash flow consequences of nine production planning strategies consisting of three master production scheduling methods and three component/part scheduling methods. Experimentation examines different operational characteristics such as demand variability, cost of capital to hold inventories and setup cost to holding cost ratios. Evaluation criteria used are characterized by total cash flow and periodic variability of cash flow to support operating expenses for each planning strategy. Simulation results indicate that sophisticated methods for planning do not necessarily cause significant savings. A second finding is that a smoother master production schedule tends to result in more stable cash outflow patterns. In comparison, component scheduling efforts are found to have relatively insignificant consequences when compared to the effects of master production schedules. [ABSTRACT FROM AUTHOR]

Frequent changes to production schedules in a material requirements planning (MRP) environment can lead to confusion at the shop floor level and reduced productivity. One approach suggested in the literature to reduce schedule instability is to introduce safety stock at the master production schedule (MPS) level to act as a buffer against differences in actual and forecast requirements. It is anticipated that, since MPg changes have a cascading effect on all lower level requirements and schedules, such a policy would help manage system nervousness. This paper examines the viability and effectiveness of using safety stock to reduce schedule instability at the MPS level. An experiment was designed to investigate the impact on schedule instability, lot-size costs, and customer service of using safety stock under a wide range of operating conditions. Five important variables characterized the environments under which the impact of safety stock was examined in this study: (1) the variation in end-item demand, (2) the uncertainty in end-item demand, (3) the item cost structure, (4) the length of the planning horizon, and (5) the lot-sizing method used. An intelligent safety stock policy was used which docs not permit scheduling of MPS completions solely for the purpose of meeting safety stock targets. The criterion variables used in this study were schedule instability, lot-size cost error, and customer service level. The primary measure of schedule instability was a weighted average of schedule changes within the planning horizon that characterized the criticality of changes by capturing the notion that it may be easier to react to schedule changes in periods of increasing distance in the future. In addition, a variety of unweighted statistics measuring the frequency and quantity of order changes were compiled for analysis. The cost error measure was a penalty cost computed as the percent deviation from the optimal total setup and carrying costs that would have been incurred by the Wagner-Whitin algorithm if demand over the entire study was known with certainty. Customer service was measured by the fill rate. The experimental results were examined using the analysis of variance procedure. The results indicate that increases in safety stock at the MPg level lead to higher customer service, but not necessarily to more stability in the production schedule or to a higher lot-size cost error. In general, the introduction of a small amount of safety stock improved schedule stability (compared to the alternative of no safety stock) and also lowered the cost error measure. However, further increases in the safety stock level often led to increases in schedule instability and always led to a higher cost penalty relative to the ex post measure of optimal cost. The increased nervousness of schedules was observed with a variety of alternative statistics that were used to measure schedule instability over the planning horizon. The results suggest that safety stock should be used with caution if it is introduced for the purpose of stabilizing schedules. In addition, the study identifies alternative strategies that may be effective in dealing with the schedule instability problem. For example, reductions in schedule instability consistently occurred when the expected time between orders was reduced and the forecast errors were low. This suggests that efforts to reduce setup costs and improve forecasting accuracy may b useful alternatives to increasing safety stock in dealing with the schedule instability problem. [ABSTRACT FROM AUTHOR]

Dealing with uncertainty in the material requirements plan (MRP) is important, because of its importance in meeting the requirements of the master production schedule (MPS). In MRP, there is a critical need to make the MPS predictable and consistent. In the early days of MRP, a philosophy of zero safety stock or safety time was rigorously advocated. It was thought to be more advantageous to eliminate the need for buffering by freezing the MPS and managing lead times to make these firm. However, it was soon recognized that it is extremely difficult, in practice, to eliminate all uncertainty that affects the MPS and its execution. Practitioners know that some level of buffering is necessary (or inevitable) given the vicissitudes of the market place, production system planning and control, and supplier performance. This article accepts these premises and proposes a model and procedures for dealing with the buffering problem and choosing optimal buffering strategies in MRP. [ABSTRACT FROM AUTHOR]

In the implementation of an MRP-based planning system it is often desirable to hold safety stocks at the component level. This approach is typical of a system that assembles finished products to order but builds components to a forecast. The same approach makes sense when end-item buffers would be prohibitively expensive to maintain, or when there is significant spares demand for the components. The existing theory for sizing component safety stocks is little more than an application of the principles governing single-level inventory decisions. The standard deviation of the distribution for demand is the key parameter. A multiple of this standard deviation, called the safety factor, is set by management policy. This safety factor determines the size of the safety stock. In simple cases there is a direct relationship between the safety factor and the level of customer service. Component commonality refers to a situation in which one component is common to more than one end item. The presence of commonality makes it difficult to determine safety stocks accurately. The existing theory, which is reviewed briefly, examines the effects of commonality on the component's safety factor. However, commonality destroys the relationship between safety factor and service level. This article introduces a simple example to illustrate this fact. The example suggests some problems that must be addressed if the theory is to encompass commonality. Among these are the need to develop service level measures for multiple products and to analyze the relationship between safety stock and service level. [ABSTRACT FROM AUTHOR]

Lead times in MRP systems represent the planned amount of time allowed for orders to flow through the manufacturing system. Setting lead times is a major issue in the operation of MRP systems. There exists, however, very little documentation on just how lead times should be set. This study examines the effects lead times have on MRP-based manufacturing logistics systems. In particular, it examines the effects that lead times have on backlogs, order tardiness, and finished component inventories. A major finding is that changes to the level of planned lead times have both transient and steady state effects that may not necessarily operate in the same direction. A simple methodology is presented for setting the level of planned lead times when the criterion is finished component inventory. [ABSTRACT FROM AUTHOR]

Material requirements planning (MRP) is a planning and information system that has widespread application in discrete-parts manufacturing. The purpose of this article is to introduce ideas that can improve the flow of material through complex manufacturing systems operating under MRP, and that can increase the applicability of MRP within diverse manufacturing environments. MRP models the flow of material by assuming that items flow from work station to work station in the same batches that are used in production. That is, once work starts on a batch of a certain item at a certain work station, the entire batch will be produced before any part of the batch will be transported to the next work station on its routing plan. Clearly, efficiency can be increased if some parallelism can be introduced. The form of parallelism investigated here is overlapping operations. Overlapping operations occurs when the transportation of partial batches to a downstream work station is allowed while work proceeds to complete the batch at the upstream work station. The potential efficiencies to be gained are the following:• Reduced total lead time • Reduced work-in-process inventory • Reduced floor space requirements • Reduced size of transfer vehicles Additional costs may accrue through additional cost of transportation of partial batches and through additional costs of control. Some MRP software vendors provide the data processing capability for overlapping operations. However, the user is given little or no guidance on overlapping percentages or amounts. It is our intent to provide a simple, robust technique to MRP users who would like to overlap operations and gain some or all of the above efficiencies. An optimal lot-sizing technique is derived by considering a generic two work station segment of a manufacturing system. Under the assumptions of constant demand and identical production rates, a cost function that considers setup costs, inventory holding costs and transportation costs is derived. This cost function is minimized subject to the constraint that the production batch is an integer multiple of the transfer batch. We solve for the optimal production batch, the optimal transfer batch, and the integer number relating them. Solutions are obtained as closed form, easyto-evaluate formulas. By introducing more parallelism, overlapping operations can reduce lead time. However, this will not happen without modification of MRP logic to accommodate such reduced lead time. We derive a formula that shows how a significant lead time compression can easily be obtained and implemented in MRP. We consider an example to illustrate the application of the technique on typical data from the electronics industry. The outcome showed a cost savings of approximately 22.5% over the standard MRP approach. Overlapping operations allows the applicability of MRP to an increasing number of situations that are not modeled faithfully by conventional MRP logic. Three such situations that occur olden are the following: • Limited floor space prohibits storage of production hatches in work station output buffers. • Limited size of transfer vehicles dictate that several transfers should be planned. • Lead time requirements prohibit nonoverlapped operations. Our analysis suggests how to accommodate these difficult practical situations into MRP. Overlapping operations in material requirements planning provides an enhancement that allows wider applicability, shortened lead times, and lower total costs. It may be applied selectively to any two work stations where it is deemed appropriate. Due to the structure of the cost function, it is possible to make the transfer lot-sizing decisions independent of the production lot-sizing decisions. Therefore, significant improvements can be made through overlapping with minimum disruption to the existing MRP system machinery. It is our conviction that overlapping operations is an important concept that can and will impact MRP. We suggest the approach presented here as a systematic way to implement overlapping. [ABSTRACT FROM AUTHOR]

This article addresses the question of accuracy of planned lead times (PLTs) that are used with a material requirements planning system. Lead time error is defined as the difference between an item's PLT and the actual lead time (flow time) of an order to replenish the item. Three related topics are discussed: the relationship between system performance and average lead time error, the transient effect on work-in-process (WIP) inventory of increasing PLTs, and the relative accuracy of three methods of determining PLTs. A distinction is made between available and WIP inventory. The former includes any purchased item, fabricated part, assembly, or finished good that is in storage and available for use or delivery. WIP denotes materials associated with open orders on the shop floor. It was concluded that average lead time error has a considerable affect on system performance. PLTs that are on average too long or too short increase available inventory; and the further the average error is from zero, the more pronounced the increase. Contrary to conventional wisdom, increasing PLTs will increase the service level (decrease backorders), unless PLTs are already severely inflated and MPS uncertainty (forecast error) is small. If PLTs are inflated, decreasing them will decrease the number of setups per unit time in the case of considerable demand uncertainty. Contrary to conventional wisdom, increasing PLTs causes only a transient rise WIP inventory. The fact that the average lead time error has a significant effect on the three areas of system effectiveness mentioned above does not imply that a given order's lead time should be managed in a way that forces its actual lead time to match the PLT. Stated another way, the material planner may use the latest information to manage a given order's lead time; however, if the average discrepancy between the actual and planned lead times is large, system performance can be improved by changing the PLTs to approximate the average flow times. Three methods that have been proposed for determining PLTs are compared. They are historical averages of the actual flow times, calculated lead times based on standard times and historical averages of the queuing time at the appropriate work centers, and the QUOAT lead time proposed by Hoyt. The third was found to perform poorly unless the work content of all operations is identical. With one exception, no differences were found between the first two methods. The simpler historical average method was superior to the calculated lead time in the case where the work content of each operation varies and when considerable demand uncertainty exists. The results are based on simulation experiments employing a generalized MRP/Job-Shop stochastic simulation model. The program launches orders based on standard MRP logic, reschedules open orders by moving the due date in or out to coincide with revised need dates, moves manufacturing orders through a job shop, schedules the delivery of purchase orders, and updates inventory levels. The product structure tree contained eight distinct items, with four levels and one end item. There is no reason to believe that the conclusions would be any different had a larger system been studied. [ABSTRACT FROM AUTHOR]

The problem of determining the appropriate stock replenishment quantity within a time-phased requirements planning environment has received considerable research attention in recent years. Relative performance characteristics of lot-sizing policies have been assessed as a function of the cost structure, the demand pattern, the product structure, forecast error, the length of the planning horizon, and the interaction between replenishment quantities and sequencing decisions. In particular, the relationship between lot sizing behavior and variability in the requirements profile has been intensely investigated. However, despite these efforts, the empirical evidence linking lotsizing performance with demand variability remains inconclusive. This article suggests that, in part, some of the ambiguity in the literature may be an artifact of a failure to adequately control for other important dimensions of simulated demand sequences. The features that have been thought to describe "lumpy" requirements profiles are discussed and the characteristic of periodicity or time-dependency in the demand entries is identified as a variable that has been insufficiently controlled in prior work. A reanalysis of the demand sequences originally published by Kaimann, and subsequently used in a number of comparative lot-sizing studies, reveals that the patterns differ not only in variability as measured by the coefficient of variation, but also in terms of correlation structure as described by the autocorrelation function. Alternative methods for simulating demand sequences are reviewed and a correlation transfer technique, which has the capability to simultaneously control both the degree of variability and correlation, is suggested as an improved method for the generation of synthetic sequences of "lumpy" demand. Using this technique, five of Kaimann's original sequences are rearranged, resulting in three sets of sequences differing only in the strength of serial correlation. Four lot-sizing procedures are applied to each of these sets to discern if the correlation structure has any appreciable effect on lot-sizing performance. Results indicate that, on average, higher total inventory costs are experienced when the demand environment is characterized by randomness. Economic order quantity and partperiod balancing achieve lowest average costs when confronted with highly autocorrelated demand or patterns of few runs; conversely, minimum cost per period and Wagner-Whitin perform best under conditions of many runs. Both economic order quantity and part-period balancing perform most favorably in comparison to Wagner-Whitin when runs are few. In addition, there appears to be a potential interaction between the level of demand variability and the degree of serial correlation. This finding is somewhat disconcerting since high variability demand sequences used in some prior research were also characterized by relatively high levels of autocorrelation; hence it becomes most difficult to identify and decompose the unique influences of each demand pattern dimension on lot-sizing behavior. Because of this phenomenon, it is suggested that future studies direct greater attention to the demand simulating methodology than has heretofore been accorded. [ABSTRACT FROM AUTHOR]

Due to the uncertainty in estimating both the demand for end products and the supply of components from lower levels, buffering techniques should be included before the loading of a material requirement planning (MRP) system. Safety stocks and safety lead time are two techniques of providing buffering for loading. There have been many studies made concerning the determination of the amount of safety stocks and safety lead time. Some guidelines for choosing between safety stocks and safety lead time for dealing with uncertainty in both demand and supply also have been established. Although these two different methods have been used successfully, it has not been documented that using these two methods in a given situation will yield essentially the same results; that is, the interchangeability of these two buffering techniques has not been explored quantitatively. Since the net influence of safety stocks and safety lead time and their quantitative interchangeability are of major interest, an analytical model is proposed for this study. The lead-time offset procedure for components loading are represented by a matrix model that is based on a lot-for-lot lot-sizing technique. This lead-time offset matrix model is the product of the precedence matrix and the fixed-duration matrix. The precedence matrix is formed according to the total requirement factor matrix and the duration matrix is formed by each component process time. Thus, the lead-time offset matrix will generate the starting period of each component. When the lead-time offset procedure is modeled, the net influence of buffering quantity can be analyzed. The planned safety stock that is normally used to accommodate unexpected demand, shortage in supply, and defects from the operation at each process can be combined with demand to form the master production schedule. The revised lead time due to the integration of the safety stocks can be calculated through the lead-time offset model. The safety lead time may extend the component process time as well as overall production lead time if the designated safety lead time is longer than the available slack time in a fixed lead-time loading system. When the proposed lead-time offset model is further examined, it is found that planned safety stocks at the higher level can buffer the fluctuations of lower level components quantity as well as the fluctuations of same level components quantity. Safety stocks can also buffer shortages that are caused by the delay of raw material and manufacturing processes. Thus, safety stocks can be used to buffer unexpected delay time up to certain limits. A planned safety lead time at higher level component process can buffer the fluctuations of lower level components process time, as well as the same level component process time. The safety lead time can be used to produce additional products to meet unexpected excessive demand up to certain limits under the following conditions: 1. The excessive demand is known before the actual processing of the components in the lowest level. 2. The raw material at the lowest level is available. Although safety stocks and safety lead time are interchangeable in terms of the ability to buffer variations in quantity, the conditions for safety lead time are seldom met in actual practices. Thus, the slack time in a fixed lead-time loading system cannot be considered as an effective measure to substitute safety stocks. However, all or part of the delay in manufacturing processes or the supply from the lower level components can be buffered by the safety stock and the MPS will still be met. From this study, it is obvious that the slack time can be reduced when safety stocks are planned for an MRP system. The reduction of fixed lead-time duration will be beneficial to the overall planning and scheduling in MRP systems. [ABSTRACT FROM AUTHOR]

Considerable research effort has been spent on production planning in multilevel product structures. The foundations for this research come from the multi-echelon inventory literature developed by Zangwill, Veinott, Scarf, Clark, and many others. Researchers have begun to consider questions related to the management of complex product structures, including multiple products and commonality. Much of the motivation for addressing these later research issues has come from the prevalent use of Material Requirements Planning (MRP) for controlling production in a multilevel, multiproduct environment. Although the focus in MRP research has remained on tactical issues, this study will deal with several broader issues by analyzing some very simple product structures in order to make clear statements concerning the performance of selected production strategies. The major research question considered in this study involves the effect of commonality on system performance under various production planning strategies. The strategies include the two pure approaches of make-to-stock and make-to-order and the hybrid assemble-to-order strategy, which is a combination of make-to-order and make-to-stock. Performance measures of importance are total cost of operation (set-up and holding costs) and the variance in work-in-process inventories. These have been selected because of the concern among practitioners to reduce costs of operation as well as the degree of variability in shop floor loads. For the purposes of comparison, a mixedinteger programming solution to the various experimental conditions is determined. The major results of a four-way analysis of variance that includes production strategy, level of commonality, cost ratio (set-up to holding cost), and random-demand streams as experimental factors, follows: 1. High commonality models are less cost sensitive to the production strategy applied than low commonality models. 2. High commonality can lead to high load variation particularly at lower levels of the product structure. 3. The choice of a production strategy becomes more cost sensitive as cost ratios (set-up to holding) increase. 4. Product structures with low cost ratios are less sensitive to load variation than those with high ratios. [ABSTRACT FROM AUTHOR]

Available lot sizing rules for use in MRP (Material Requirements Planning) systems ignore capacity limitations at various work centers when sizing future orders. Planned order releases are instead determined by the tradeoff only between the item's set up and inventory holding costs. This limitation can cause unanticipated overloads and underloads at the various work centers, along with higher inventories, poorer customer service, and excessive overtime. This research explores one way to make MRP systems more sensitive to capacity limitations at the time of each regeneration run. A relatively simple heuristic algorithm is designed for this purpose. The procedure is applied to those planned order releases that standard MRP logic identifies as mature for release. The lot sizes for a small percentage of these items are increased or decreased so as to have the greatest impact in smoothing capacity requirements at the various work centers in the system. This algorithm for better integrating material requirements plans and capacity requirements plans is tested with a large scale simulator in a variety of manufacturing environments. This simulator has subsequently undergone extensive tests, including its successful validation with actual data at a large plant of major corporations. Simulation results show that the algorithm's modest extension to MRP logic significantly helps overall performance, particularly with customer service. For a wide range of test environments, past due orders were reduced by more than 30% when the algorithm was used. Inventory levels and capacity problems also improved. Not surprisingly, the algorithm helps the most (compared to not using it at all as an MRP enhancement) in environments in which short-term bottlenecks are most severe. Large lot sizes and tight shop capacities are characteristic of these environments. The algorithm works the best when forecast errors are not excessive and the master schedule is not too "nervous." This proposed procedure is but one step toward making MRP more capacity sensitive. The widely heralded concept of "closed-loop" MRP means that inventory analysts must change or "fix up" parts of the computer generated material requirements plan. What has been missing is a tool for identifying the unrealistic parts of the plan. Our algorithm helps formalize this identification process and singles out a few planned order releases each week. This information comes to the analyst's attention as part of the usual action notices. These pointers to capacity problems go well beyond capacity requirements planning (CRP) and would be impossible without computer assistance. Our study produced two other findings. First, short-term bottlenecks occur even when the master production schedule is leveled. The culprits are the lot sizing choices for items at lower levels in the bills of material. "Rough-cut" capacity planning, such as resource requirements planning, therefore is not a sufficient tool for leveling capacity requirements. It must be supplemented by a way to smooth bottlenecks otherwise caused by shop orders for intermediate items. Second, the disruptive effect of large lot sizes is apparent, both in terms of higher inventories and worse customer service. Large lot sizes not only inflate inventories, but paradoxically hurt customer service because they create more capacity bottlenecks. The only reason why management should prefer large lot sizes is if set-up times are substantial and cannot be efficiently reduced. This finding is very much in step with the current interest in just-in-time (JIT) systems. [ABSTRACT FROM AUTHOR]

Many manufacturing firms have multiple manufacturing plants, located in geographically diverse parts of the world. This situation is becoming more common, as firms establish new plants in foreign countries to take advantage of low labor cost. In such cases, it is not unusual for the firm to retain production capability of certain key parts in a backup plant, with the necessary equipment and trained workforce in place. High volume production could be obtained relatively quickly from the backup plant in case of an emergency at the main supplying plant. In such multiplant settings, the transportation costs are significant. Throughout this paper, we use the term "multisourced parts" to describe parts produced in more than one location. Material Requirements Planning (MRP) is the component of a total manufacturing control system that is designed to manage inventory and plan orders for parts and material with dependent demand (demand derived from the demand of other items). Most of the literature on MRP systems discusses MRP methodology in a single-plant environment. Most MRP software systems in use today are single-plant systems. Currently, it is common for firms with multiple plants treated as cost centers to use an independent single-plant MRP system for each and handle the transshipment problems manually. Because of lack of coordination of production schedules between supplying and demanding plants, those firms hold more inventory and experience longer lead times than necessary to compensate for uncertainties in schedules and supply policies. The purpose of this article is to enhance single-plant MRP systems for coping with multiplant situations in which: the plants are regarded as cost centers, there exist multisourced parts, and the transportation costs are significant. The multiplant MRP system should recognize that pans are produced in different plants, make offset calculations for in-transit lead times, and consider transportation costs when establishing production requirements and shipping routes for multisourced parts. The objective is, beginning with the corporate-determined master schedule for finished products, to communicate in one planning cycle time-phased planned order release schedules and shipping/delivery schedules to each manufacturing plant producing components for the finished products. We first present a simplified framework for the multiplant MRP system, where a transportation algorithm is incorporated into the MRP logic. Then we refine this simplified framework to handle more complex aspects of a multiplant network. These complexities include the treatment of requirements that are not shipped on time and the regeneration of new MRP schedules. We also observe that the solution to the transportation problem described above is affected by the lot-sizing rules employed. In addition, we discuss several important issues and decisions that confront a firm when implementing a multiplant MRP system. [ABSTRACT FROM AUTHOR]

Much of the current literature in the field of production and inventory control systems stresses the need to revise traditional forms of thinking regarding production processes, the role of inventories for work in process, and the need for reduced lead times or flow times. Group technology, manufacturing cells, and other means of incorporating repetitive manufacturing techniques into traditional job-shop settings constitute the leading edge in system development. Still, there is resistance to these dramatic changes, and traditional "business as usual" methods still predominate. This study attempts to illustrate graphically the cost justification associated with reduction in lead times which generally results from these new concepts. In most job shops today, lead times are much longer than they need to be due to inflation of lead time estimates. Actual lead times for the manufacture of fabricated and assembled products have been shown to be a direct consequence of the planning lead times used in the MRP planning process—a form of self-fulfilling prophesy. The research employs a simulation model of a factory using MRP as a planning tool in a multiproduct, multilevel production environment. Manufacturing costs constitute the dependent variable in the experiments, defined as the sum of material costs (including expedite premiums), direct labor costs (including overtime premiums), inventory carrying costs, and overhead costs. The independent variable being manipulated is the planned lead time offset used in the MRP planning process. Twenty values of planned lead time are evaluated ranging from a value that includes no slack time at all (pure assembly line) up to a value that allows 95% slack (queue) time which, unfortunately, is not uncommon in many job shops today. Stochastic variables in the model include customer demand and actual processing times—the sum of set-up and run times. The result of the study is a cost curve formed over the range of independent lead time variables that is constructed using nonlinear regression techniques. The conclusions from the resultant graph clearly indicate the cost consequences of long lead times, with exponential cost increases beyond the 80-90% queue time level. Total costs are 41% higher at the maximum lead time allowance compared to the minimum. Clearly, this study demonstrates the need for lead time reduction, either through downward adjustment of MRP planned lead times or by introducing new manufacturing concepts. [ABSTRACT FROM AUTHOR]

This paper examines the effectiveness of three commonly practiced methods used to resolve uncertainty in multi-stage manufacturing systems: safety stock under regenerative material requirements planning (MRP) updates, safety capacity under regenerative MRP updates, and net change MRP updates, i.e., continuous rather than regenerative (periodic) updates. The use of safety stock reflects a decision to permanently store materials and labor capacity in the form of inventory. When unexpected shortages arise between regenerative MRP updates, safety stock may be depleted but it will be replenished in subsequent periods. The second method, safety capacity, overstates the MRP capacity requirements at the individual work centers by a prescribed amount of direct labor. Safety capacity either will be allocated to unanticipated requirements which arise between MRP regenerations or will be spent as idle time. The third method, net change, offers a means of dealing with uncertainty by rescheduling instead of buffering, provided there is sufficient lead time to execute the changes in the material and capacity plans. Much of the inventory management research has addressed the use of safety stock as a buffer against uncertainty for a single product and manufacturing stage. However, there has been no work which evaluates the performance of safety stock relative to other resolution methods such as safety capacity or more frequent planning revisions. In this paper, a simulation model of a multistage (fabrication and assembly) process is used to characterize the behavior of the three resolution methods when errors are present in the demand and time standard estimates. Four end products are completed at an assembly center and altogether, the end products require the fabrication of twelve component parts in a job shop which contains eight work centers. In addition to the examination of the three methods under different sources and levels of uncertainty, different levels of bill of material commonality, MRP planned lead times, MRP lot sizes, equipment set-up times and priority dispatching rules are considered in the experimental design. The simulation results indicate that the choice among methods depends upon the source of uncertainty, and costs related to regular time employment, employment changes, equipment set ups and materials investment. For example, the choice between safety stock and safety capacity represents a compromise between materials investment and regular time employment costs. The net change method is not designed to deal effectively with time standard errors, although its use may be preferred over the two buffering alternatives when errors are present in the demand forecasts and when the costs of employment changes and equipment set ups are low. The simulation results also indicate that regardless of the method used, efforts to improve forecasts of demands or processing times may be justified by corresponding improvements in manufacturing performance. [ABSTRACT FROM AUTHOR]

Certain manufacturing systems, notably those in high technology precision casting and integrated circuit production suffer from process yield losses which are both significant in quantity terms and are also highly unpredictable. This poses special problems for the provisioning of materials to support a manufacturing program and for the detailed scheduling necessary to update the priorities of work in process batches as losses occur. This paper establishes a framework of analysis to handle this problem in MRP logic. It describes the mechanisms available and discusses their relevance to the market environments in which the company is operating. The key conclusion of this paper is that different solutions are required for different market circumstances. The four key strategies developed are: A: For continuous schedules, make-for-stock: Use mean yield rate and fixed buffer stocks. B: For continuous schedules, make-to-order: Use mean yield rate, fixed buffers and a yield to finish monitoring system. C l: For single batch production make-to-order: As for B but using a desired service level yield rate. C2: For multiple batch production, make-to-order: As B but using a variable yield rate by batch. The implementation of each of these is described in relation to the business objectives of cost effectiveness and customer satisfaction. [ABSTRACT FROM AUTHOR]

Constrained resource project scheduling techniques schedule project activities subject to finite constraints on the availability of non-storable resources such as labor and equipment without consideration of constraints resulting from material requirements. Projects are frequently delayed and resources are wasted when project activities are delayed due to material shortages. A heuristic procedure is presented here for scheduling large projects subject to the availability of all necessary resources, including materials, manufactured components, facilities, equipment and labor as well as the acquisition lead times required by these resources. Results are listed for tests involving both benchmark and actual problems. [ABSTRACT FROM AUTHOR]

This paper evaluates conventional lot-sizing rules in a multi-echelon coalescence MRP system. A part explosion diagram of three levels and twenty-one nodes is simulated using FORTRAN IV Level G. Nine separate lot-sizing methods were evaluated in this analysis. These methods included Lot for Lot, Economic Order Quantity, Periodic Order Quantity, Least Total Cost, Least Unit Cost, Part-Period Balancing, the Silver-Meal Algorithm, and the Wagner-Whitin Algorithm. A hybrid rule using both the Economic Order and the Economic Production Quantity rules was also evaluated. The performance of each lot sizing rule was simulated over nine different sets of market requirements patterns over a twelve month period. The types of demand variation included a constant rate, three different patterns of normally distributed demand, a random pattern, and two cyclic patterns. A hybrid pattern was used which equally weighted components of constant, random, normal, and cyclic demand. Finally, the ninth pattern consisted of actual data obtained from a job shop manufacturing facility. Within the part explosion diagram, ratios of setup cost to carrying cost, "goes into" quantities, and lead times were assigned for each node. Assigned values were selected from uniform distributions with prespecified ranges. A computer model was developed to perform the simulation. It consisted of an executive program, a routine for data generation, and separate routines to exercise each of the different lot-sizing rules. The simulations were conducted under three operational rules. The first rule allowed for the establishment of initial inventories just large enough to "cover" those gross requirements that occurred prior to the time the first order arrived. Carrying costs for this stock were included in the computation of total costs per node. The second rule provided for the delay of application of each lot sizing rule. This avoided receiving an order in a period of zero demand. The third rule addressed the computation of costs. The total cost was computed on the basis of average inventory level and the number of required setups. The analysis required the completion of 1701 separate simulation runs (9 rules × 9 demand patterns × 21 nodes). The performance of each rule was evaluated on the basis of total annual inventory cost. The Periodic Order Quantity (POQ) rule performed best in six of the nine demand patterns analyzed. In two of the remaining three cases, it ranked second on the basis of minimizing costs. The Least Unit Cost (LUC), Least Total Cost (LTC), and Part-Period Balancing (PPB) algorithms demonstrated identical performance in four of the demand patterns analyzed. Generally, they ranked in the upper half of the rules evaluated. The Economic Order Quantity (EOQ) and the Economic Order/Production Quantity hybrid rules performed only moderately well. On the basis of cost, the consistent worst performers were the Wagner-Whitin (WW), Silver-Meal (SM), and Lot-for-Lot (LFL) rules. It was found that gross requirements tend to occur sporadically in different levels of the system. Order policies of parent nodes often cause the policies in higher level nodes to resemble the lot-forlot order philosophy, regardless of the rule being used. Because of this phenomenon, those rules that generate fewer orders over the planning horizon for parent nodes often tend to perform better on the basis of total inventory cost. [ABSTRACT FROM AUTHOR]

Material Requirements Planning (MRP) systems have been widely applied in industry to better manage multiproduct, multistage production environments. Although many applications have been quite successful, much is still left to the planner's intuition as to how to assure that master schedules, component lot sizes, and priorities realistically conform to the capacity limits at individual work centers. Capacity issues may indeed be the soft spot in MRP logic. This paper explores some possible causes of irregular workload patterns when using an MRP system. Better insight on which factors cause temporary bottlenecks could help managers better assess the vulnerability of their plants to this problem. It might also suggest ways of dampening peaks and valleys. The problem setting is a multistage environment; several products are made from various subassemblies and parts. Each shop order is routed through one or more capacitated work centers. An order is delayed either by temporary capacity shortages or the unavailability of components. Of course, the second delay can be caused by capacity problems previously encountered by the shop orders of its components. Seven experimental factors are tested with a large-scale simulator, and five performance measures are analyzed. The factors are the number of levels in the bill of material, the average load on the shop, the average lot size, the choice of priority rule, demand variability, the use of a gateway department, and the degree of equipment specialization. We have one measure of customer service, two for inventory, and two for workload. The workload measures are unconventional, since our interest is when workload variability occurs and how it affects inventory and customer service. The simulator has been developed over the course of eight years, and since this study has been further enhanced to handle many more factors. The simulator was validated recently with real data at two manufacturing plants. It is quite general, in that the bills of material, shop configuration, routings, worker efficiencies, and operating rules can be changed as desired. An initial screening experiment was performed, whereupon the average load and priority rules were not statistically significant at even the .05 level. A full factorial analysis with two replications was then conducted on the five remaining factors. Multivariate analysis of variance (MANOVA) and analysis of variance (ANOVA) statistical tests have been performed. The results confirm that workload variability can have a detrimental impact on customer service and inventory. The following structural changes to the manufacturing system can be beneficial, but tend to be more difficult to achieve. More BOM levels improve customer service, but increase inventory and capacity bottlenecks. Resource flexibility is a powerful tool to reduce workload variability. Capacity slack averaging much over 10% is wasteful, having no benefits for inventory and customer service. In general, revising the routing patterns only, such as creating more dominant paths, will not give big payoffs. The following procedural changes are easier to implement. Master schedules which smooth aggregate resources are an excellent device to reduce workload variability. Even with a smooth MPS, debilitating workload variability can still occur due to the design of the BOM, lot size, and leadtime offset parameters. Selecting a priority rule does not seem to be of overriding importance compared to master scheduling and component lot sizing. These findings must be considered within the context of the range of plant environments encompassed by this study. [ABSTRACT FROM AUTHOR]

The problem to be considered is that of determining lot-sizes for a group of products which are produced at a single workcentre. It is assumed that the requirements for each product are known, period by period, out to the end of some common time horizon. (A reasonable assumption in a Material Requirements Planning context when we are dealing with components of one or more other items already scheduled.) For each product there is a fixed setup cost incurred each time production takes place. Unit production and holding costs are linear. The time required to set up the machine is assumed to be negligible. All costs and production rates can vary from product to product but not with respect to time. In each period there is a finite amount of machine time available that can vary from period to period. The objective is to determine lot-sizes ... I) costs are minimized, 2) no backlogging occurs and 3) capacity is not exceeded. An exact solution to this complex problem is out of the question. Therefore, a simple heuristic has been developed which guarantees a feasible solution, if one exists. Results of a large number of test problems, including three supplied by industrial sources, are presented. The results indicate that the heuristic will usually generate a very good solution with a relatively small amount of computational effort. [ABSTRACT FROM AUTHOR]

Master production scheduling, component lot sizing, and capacity requirements planning represent three important modules of material requirements planning (MRP) systems. Coordinating these three, modules has been largely dependent on managerial judgment and experience. In this research, five different strategies for integrating these modules are empirically investigated, These strategies differ mainly in the extent to which the modules are coordinated. The impact of the shop, product, component and cost characteristics is measured by varying ten experimental factors. The research findings so obtained provide several guidelines on the effectiveness of each strategy in different environmental settings. [ABSTRACT FROM AUTHOR]

Substantial interest has been focused on techniques that determine the amount and timing of work center capacity to satisfy the master production schedule. Although several techniques have been developed for preparing work center capacity plans, very little analysis of the operational features and the application of these techniques has been reported. Four techniques, capacity planning using overall factors (CPOF), capacity bills, resource profiles, and capacity requirements planning (CRP), vary substantially in their complexity and the level of detail required to plan work center capacities. All four procedures require the use of the master production schedule to develop a capacity plan, but some have much more demanding data requirements. Important differences are the means by which capacity requirements are estimated by the techniques and the manner in which the bill of material, manufacturing lead time and inventory status information are incorporated into the capacity plan. The purpose of this paper is to describe the operational features of the four capacity planning techniques, the underlying data base requirements, and some key managerial issues in choosing among these techniques. [ABSTRACT FROM AUTHOR]

U.S. industry has been bombarded with prescriptions for catching up with the Japanese. Surprisingly absent from many lists of these prescriptions is the Japanese just-in-time (JIT) production system. The JIT approaches are simple and generally require little use of computers, and they appear to provide far tighter controls on inventory than are attainable via U.S. computer-based approaches. More importantly, Japanese JIT tends to promote major improvements in quality and productivity, as well as increased worker responsibility and commitment. JIT applications and benefits apply not only to the shop floor but also to the distribution and the purchasing ends of the business. In the article, JIT is contrasted with MRP, and the JIT production system is explained with reference to a graphical cause-effect model. The necessity, under the JIT system, of revising traditional assumptions with regard to cycle stock and buffer inventories is explained. The author's views on how JIT affects plant configurations are presented, along with personal observations on how one Japanese subsidiary in the U.S. has been reconfiguring its plant in the process of adopting a JIT production system. [ABSTRACT FROM AUTHOR]

A heuristic algorithm is developed and applied to determine lot sizes and production sequence on a single facility. The various product demands are treated as deterministic and time varying (dynamic) over a finite planning horizon, such as that generated from a material requirements planning (MRP) system. In contrast to other approaches available, the algorithm considers the sequencing decision in each period by realistically assuming inventory homing cost occurrence in the period of production, and in addition, it is capable of considering set-up times where such set-up times consume available productive capacity. The ability to handle numerous products, and the capability of being able to specify maintenance time and holidays is an integral aspect of the algorithm. The results of an application of the algorithm in a medium size bearing company have shown very significant reduction in the controllable inventory holding cost while eliminating late deliveries. In an effort to cope with potential realistic schedule alterations, different solutions were developed for managerial evaluation providing greater flexibility but at a higher cost. [ABSTRACT FROM AUTHOR]

This paper reports on a large-scale survey of companies involved in MRP implementation. Survey responses are used to develop a profile of problems typically encountered during the implementation process. Discriminant analysis is used to determine which of those problems, and additional factors, appear to affect the success or failure of MRP implementation. Finally, comparisons are made between the problems encountered during implementation and problems which were found to significantly discriminate between successful and unsuccessful MRP implementors. [ABSTRACT FROM AUTHOR]

What lot size model(s) to use in a Material Requirements Planning (MRP) system is an unresolved and often debated issue. The concept of dependent demand, the complex network defined by the product structure, the dynamics of an operating MRP-based system, and the subsequent use of the planned order release schedule by other company subsystems represent a totally new environment for making and managing lot size decisions. The purpose of this paper is to identify and briefly examine ten research issues related to lot sizing in a dependent demand product structure. These ten issues expand the solution space for lot sizing in an MRP-based system compared to a reorder point based system. Areas for further research are suggested. [ABSTRACT FROM AUTHOR]

The difficulty of implementing planned change in an organization is legend. In the last 20 years the implementation of computer based models and systems in particular has received a significant amount of attention in the form of hundreds of conference presentations, published case studies, and research reports. Yet, system implementation failures are still prevalent. This paper surveys the implementation literature primarily in three fields: management information systems, operations research/management science, and production-inventory management. Common difficulties are identified and managerial proverbs, consultants' insights, statistically verified procedures, research conclusions, and other such documented wisdom for improving the chances of implementation are analyzed. A classification scheme is developed which divides this documented material into three diverse categories of pitfalls in implementation. These categories are then discussed from the perspective of providing managers with the information needed to analyze their own organization in terms of the likelihood of successfully implementing such computer based information systems as Material Requirements Planning (MRP). [ABSTRACT FROM AUTHOR]

This paper describes benefits and costs of MRP systems based on a large survey of MRP users. These users report they have achieved significant improvements in inventory turnover, delivery performance, and other benefits, and that further improvements are expected when their MRP systems are fully implemented. A series of regression models are also described in the paper which explain why some companies achieve more benefits from MRP than others. The models are not only fitted to the sample data, bat they obtain good predictive results on a holdout sample. These models indicate that companies should stress a broad approach to implementation; there is no one overriding factor which guarantees MRP Success. [ABSTRACT FROM AUTHOR]

Capacity management is the planning and leveling of resources required (load) against the resources available (capacity). In this study, the lot size models used by Material Requirements Planning (MRP) had a major effect on the work center load profiles generated by Capacity Requirements Planning (CRP). Therefore, the selection of lot size models for MRP systems is an important decision for capacity management as well as materials management. The results of this study highlight the operating characteristics of specific lot size models considering setup, inventory carrying, and capacity associated costs. For example, the Economic Order Quantity model and the Lot-For-Lot model in certain situations can help level load. The Periodic Order Quantity and Least Total Cost models especially for high cost structure ratios tend to result in erratic and lumpy work center load profiles. The reasons for such operating behavior are examined. Other concepts and relationships important to capacity management are discussed. [ABSTRACT FROM AUTHOR]

A hybrid model combining the critical path method (CPM) with material requirements planning (MRP) has been suggested (Aquilano) as a more robust method for scheduling projects and resources. The primary advantage of this technique is that resource acquisition lead times as well as inventory records are integrated into the process of computing the project schedule. This paper presents a set of formal CPM/MRP algorithms that may be used to compute the early and late start schedules as well as the critical sequence. A number of modifications have been incorporated into the CPM/MRP technique to improve the viability of CPM/MRP as a tool for application to actual project scheduling problems. A simple example project is used to demonstrate the CPM/MRP model. The CPM/MRP technique is designed to overcome a basic shortcoming of previously suggested project scheduling methodologies. CPM was initially designed to schedule projects subject to technological constraints only. Later. additional techniques were introduced to consider constraints upon various aspects of resource availability (Davis). None of the suggested techniques attempted to integrate resource acquisition lead time with the generation of requirements for resources. Obviously such a technique would require the integration of inventory records into the scheduling technique. The combination of CPM and MRP provides a possible vehicle for overcoming this drawback in CPM. Both CPM and MRP are linear models that generate schedules based upon precedence relationships. An integrated approach is useful since activities could be scheduled subject to information about the inventory position. An activity may be scheduled as soon as all resources are on hand. It is only delayed by those resources which must be acquired and activities which preceed it in the project network. CPM/MRP also shows promise as an aid to constrained resource scheduling since computations regarding resource availability are an integrated part of the technique. The effect of resource allocation decisions is immediately evident in the MRP-type time phased records. Results of the tests run on short projects of up to 300 activities and resources have shown that the program does work satisfactorily. Execution time for a 300 item network tested was approximately ten seconds on a CYBER 175. [ABSTRACT FROM AUTHOR]

A model is formulated for computing the optimal stock quantity of an item when resupply is possible but uncertain. The distinguishing feature of the model is that the optimal stock quantity calculation takes into account the cost of resupply and the probability of stock arriving by a specified mode of transport in time for issue to customers. The model is then applied to the problem of determining a preferred mode of transport for an assumed set of parameters. [ABSTRACT FROM AUTHOR]

This note disputes several observations made by James R. Evans' article, "An Efficient Implementation of the Wagner-Whitin (WW) Algorithm for Dynamic Lot-Sizing," Journal of Operations Management, Vol. 5, No. 2, February 1985. By testing the algorithm within a micro-based manufacturing resource planning (MRP) system, the writer of this note shows that WW is still computationally burdensome compared to heuristic methods, particularly within the context of a micro-based MRP system implementation. [ABSTRACT FROM AUTHOR]

This paper reports the results of a simulation experiment that compares alternative procedures for determining purchase quantities in MRP systems when quantity discounts are available. The procedures are least unit cost (LUC), McLaren's order moment (MOM) and a "traditional" procedure that ignores the time-phased information available from an MRP system. One of the factors in the experiment was requirement uncertainty, a factor heretofore not incorporated in MRP lotsizing research. The results of the experiment confirm MOM (and to a lesser extent LUC) as an effective lot-sizing procedure. In addition, the work shows that the differences between the procedures tend to vanish as the amount of uncertainty in the requirements increases.