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This paper presents approximation methods for the performance analysis of long manufacturing lines, i.e. lines with more than two machines and one buffer, that have both quality and operational failures. We describe three different versions of long flow lines that differ in the locations of the inspection stations and in the sets of machines that each inspection station monitors. We explain a transformation method that approximates long manufacturing lines that have quality and operational failures with long lines that only have operational failures. Such lines can be evaluated by decomposition methods. We introduce other approximations to quantify the effects of the separation of inspections from operations. Comparison with simulation shows that the solution methods provide reliable performance estimates. [ABSTRACT FROM AUTHOR]

In this paper, a structure and architecture for the rapid realization of a simulation-based real-time shop floor control system for a discrete part manufacturing system is presented. The research focuses on automatic simulation model and execution system generation from a production resource model. An Automatic Execution Model Generator (AEMG) has been designed and implemented for generating a Message-based Part State Graph (MPSG)-based shop level execution model. An Automatic Simulation Model Generator (ASMG) has been designed and implemented for generating an Arena simulation model based on a resource model (MS Access 97) and an MPSG-based shop level execution model. A commercial finite capacity scheduler. Tempo, has been used to provide schedule information for the Arena simulation model. This research has been implemented and tested for six manufacturing systems, including The Pennsylvania State University CIM laboratory. [ABSTRACT FROM AUTHOR]

We present a general manufacturing-cell simulation model for evaluating the effects of world-class manufacturing practices on expected cell performance. The modular structure of the simulation provides the flexibility to analyze a wide variety of manufacturing cells. We formulate a comprehensive annualized cost function for evaluation and comparison of alternative cell configurations. A case study involving assembly of printed circuit hoards illustrates the potential benefits of using this tool for cell design and analysis. The simulation model is intended for use in a two-phase approach to cell design that is based on simulated experimentation and response surface analysis as detailed in a companion paper. [ABSTRACT FROM AUTHOR]

We present a two-phase approach to design and analysis of manufacturing cells based on simulated experimentation and response surface methodology using a general manufacturing-cell simulation model. The first phase involves factor-screening simulation experiments to identity design and operational factors that have a significant effect on cell performance as measured by a comprehensive annual cost function. In the second phase of experimentation, we construct simulation (response surface) metamodels to describe the relationship between the significant cell design and operational factors ( the controllable input parameters) and the resulting simulation-based estimate of expected annual cell cost (the output response). We use canonical and ridge analyses of the estimated response surface to estimate the levels of the quantitative input factors that minimize the cell's expected annual cost. We apply this methodology to an assembly cell for printed circuit hoards. Compared to be current cell operating policy. the simulation metamodel-based estimate of the optimum operating policy is predicted to yield average annual savings of approximately $425 000, which is a 20% reduction in annual cost. In a companion paper, we detail the structure and operation of the manufacturing-cell simulation model. [ABSTRACT FROM AUTHOR]

This paper investigates possible implementations of the autonomous agents concept in flexible manufacturing control. The implementation issues and the effectiveness of different control architectures and algorithms are analyzed by means of a simulation model of a flexible job shop. Extensive experimental results are reported, allowing the evaluation of the trade-off between the degree of autonomy and system performance. [ABSTRACT FROM AUTHOR]

This research presents guidelines to design control processes where improving quality is achieved by improving the manufacturing consistency through the use of intelligent process control. Conventional control processes cannot include the theoretical knowledge, experimental knowledge, and expert knowledge available concerning the product. A hybrid intelligent process control (IPC) combining a continuous simulation (CS) and an artificial neural network (ANN) can make this knowledge available to the operator for process control. This paper presents a methodology for combining the CS and ANN to achieve real-time process control. A human-machine interface (HMI) is included in the process to aid operators in communication with the CS/ANN hybrid IPC. The result of the new process is a real-time process control advisor (RTPCa). A case example for the methodology of formulating, formalizing, validating, and evaluating the RTPCa is given. The case studied concerns galvanizing continuous sheet steel at a steel plant. The CS is written in SIMAN, and the ANN in C. The research validates and evaluates the RTPCa using plant data, simulation output, and face validation by plant personnel. The authors conclude that the benefits of the RTPCa over other forms of IPC include better process communication to the operator, robustness to moderate changes in system parameters, the flexibility to retrain the ANN if conditions change dramatically, and the computation speed necessary for real-time process control. This methodology has further applications to other continuous processes where quality is determined by manufacturing consistency of the product, such as in the pulp paper and film processing industries. [ABSTRACT FROM AUTHOR]

This paper develops an efficient analytical method for the analysis of an n-machine production line with unreliable machines and random processing times. The behavior of the n-machine line is approximated by the behaviors of the (n - 1) two-machine lines based on the decomposition. Simulation and numerical experiment show that the analytical method works well and is very efficient. [ABSTRACT FROM AUTHOR]

In this paper, we study the effects of an imperfect production process on the optimal production cycle time. The system is assumed to deteriorate during the production process and produce some proportion of defective items. The optimal production cycle is derived, and is shown to be shorter than that of the classical Economic Manufacturing Quantity model. The analysis is extended to the case where the defective rate is a function of the set-up cost, for which the set-up cost level and the production cycle time are jointly optimized. Finally, we also consider the case where the deterioration process is dynamic in its nature, i.e., the proportion of defective items is not constant. Both linear, exponential, and multi-state deteriorating processes are studied. Numerical examples are provided to illustrate the derivation of the optimal production cycle time in these situations. [ABSTRACT FROM AUTHOR]

This paper proposes a technique for estimating steady-state quantiles from discrete-event simulation models, with particular attention paid to cycle time quantiles of manufacturing systems. The technique is based on the Cornish-Fisher expansion, justified through an extensive empirical study, and is supported with mathematical analysis. It is shown that the technique provides precise and accurate estimates for the most commonly estimated quantiles with minimal data storage and low computational requirements. [ABSTRACT FROM AUTHOR]

This paper describes an approximate analytical method for evaluating the average values of throughput and buffer levels of closed three-machine production systems with finite buffers. The method includes a new set of decomposition equations and a new building block model. The machines have deterministic processing times and geometrically distributed probabilities of failure and repair. The numerical results of the method are close to those from simulation. The method performs well because it takes into account the correlation among the numbers of parts in the buffers. Extensions to larger systems are discussed. [Supplementary materials are available for this article. Go to the publisher's online edition of IIE Transactions for the following free supplemental resource: Appendix of additional numerical results] [ABSTRACT FROM AUTHOR]

This paper focuses on the development of an integrated short-term production scheduling simulation model for a complex manufacturing operation. The decision making tool has a front-end user data interface built with Microsoft Access and Visual Basic for Applications software. The model assists production planners to make informed decisions on how best to schedule simultaneously two lanes of daily or weekly production on a unique plastic parts manufacturing line. The advantages and disadvantages (model weaknesses) of using the simulation model, especially as a scheduling tool, are discussed. In this particular application, we find that the advantages far outweigh the disadvantages. [ABSTRACT FROM AUTHOR]

Aggregate models of detailed scheduling problems are needed to support aggregate decision making such as customer order acceptance. In this paper, we explore the performance of various aggregate models in a decentralized control setting in batch chemical manufacturing (no-wait job shops). Using simulation experiments based on data extracted from an industry application, we conclude that a linear regression based model outperforms a workload based model with regard to capacity utilization and the need for replanning at the decentralized level, specifically in situations with increased capacity utilization and/or a high variety in the job mix. [ABSTRACT FROM AUTHOR]

This paper describes the development of a cohesive framework for discrete event simulation, and the embedded decision processes of a system being modeled. The work presented in the paper is an effort to develop a scientific base for simulation modeling. The paper addresses the need for separate and structured representations of physical and logical entities of a manufacturing system for simulation modeling. The formal and hierarchical constructs defined for physical and logical entities are based on a state-space representation that allows the integration of physical and logical facets in a model with varying degrees of detail. All the entities of a manufacturing system, from the most primitive to the most sophisticated, can be represented in a model by using one of the symbolic structures provided. The framework also describes the simulation dynamics by using the defined constructs. [ABSTRACT FROM AUTHOR]

In this paper, the design principles of a new knowledge-based on-line simulation (KBOLS) architecture for the purpose of integrating the supervisory decision making process with a shop floor control system is discussed. The requirements for implementing the KBOLS architecture in a computer integrated manufacturing environment are presented. The special features of the KBOLS architecture include a knowledge-based controller capable of interacting with the shop floor and a manufacturing simulator, a shared blackboard data structure for knowledge bases, and a learning module. The KBOLS architecture is implemented in a flexible manufacturing system for analyzing interruptions due to machine breakdowns and rush orders. [ABSTRACT FROM AUTHOR]

This paper considers the effects of correlated data within subgroups that have been defined for the purposes of statistical process control. Such correlation may arise if the grouping is accomplished because of simplicity in data collection, such as multiple but similar measurements on a single product or multiple station machines. The effect of correlated measurements within the subgroup is shown to increase the Type I error rate for the X chart. Variance charts are shown not to be affected in the same fashion when equality of covariances of the measurements is assumed. Monte Carlo simulation is used to show similarity of the effects on the range chart when the number of measurements in the subgroup exceeds two. Several examples are given. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to evaluate scheduling policies for the production of assembled products in an assembly shop. The scheduling policies examined include duedate assignment, labor assignment and item sequencing rules. The sensitivity of these rules to product structure is also considered. The data for analysis is generated by a SLAM II simulation model of a hypothetical dual constrained assembly shop operation. The 2 · 3 · 3 · 3 complete factorial experiment is analyzed by an ANOVA procedure to statistically determine whether job structure, duedate assignment rule, labor assignment rule and item sequencing rule or their interaction significantly affect the root mean square of tardiness of jobs completed by the assembly shop. Further analysis to identify where significant differences in performance occurs is conducted via Tukey multiple comparison tests and general linear contrasts. [ABSTRACT FROM AUTHOR]

Analytical models of multi-product manufacturing systems operating under CONWIP control are composed of closed queuing networks with synchronization stations. Under general assumptions, these queuing networks are hard to analyze exactly and therefore approximation methods must be used for performance evaluation. This research proposes a new approach based on parametric decomposition. Two-moment approximations are used to estimate the performance measures at individual stations. Subsequently, the traffic process parameters at the different stations are linked using stochastic transformation equations. The resulting set of non-linear equations is solved using an iterative algorithm to obtain estimates of key performance measures such as throughput, and mean queue lengths. Numerical studies indicate that the proposed method is computationally efficient and yields fairly accurate results when compared to simulation. [ABSTRACT FROM AUTHOR]

In this paper an analytical approximation for the performance of non-homogenous asynchronous Flow Production Systems (FPSs) with finite buffers is presented. Generally distributed stochastic processing times as well as breakdowns and imperfect production are considered. The procedure explicitly accounts for simultaneous blocking and starving. The approximation is based on the decomposition of an M-station-line into M -- 1 two-station-lines which are analyzed with the help of a GI/G/ I /Nmax queueing model. Numerical comparisons with exact and simulation results for hypothetical as well as for real-life flow-lines indicate that the procedure provides accurate results. [ABSTRACT FROM AUTHOR]

Collision detection is a critical aspect of Virtual Reality (VR)-based simulation of manufacturing processes. Despite the significant progress that has been made in developing efficient, exact collision detection algorithms for convex objects, limited and slow progress has been reported in developing collision detection algorithms for general, nonconvex objects. To narrow this gap we introduce the concept of virtual objects which extends the applicability of exact collision detection algorithms to nonconvex objects. The outcome of our methodology is the fast creation of convex objects for a class of frequently encountered nonconvex manufacturing objects that can be used in any existing collision detection approach. The collision detection technique described in this paper is best suited for interactive simulation and animation applications where a high accuracy of object contact modeling is required. Examples include virtual assembly; mobile robot simulation; robotic painting; robotic welding; and coordinate measuring processes. [ABSTRACT FROM AUTHOR]

We present a mathematical programming approach for simulation and optimization of a general continuous-flow production system with an intermediate finite buffer. In this system, each station is represented with a discrete state space-continuous time process with given transition time distributions between the states and a set of flow rates associated with each discrete state. We develop a mathematical programming formulation to determine the critical time instances of the sample trajectory of the buffer that correspond to state transitions, buffer dynamics, and changing flowrates. We showthat a simulated sample realization of the systemis obtained by solving amixed-integer linear program. The mathematical programming representation is also used to show that the production rate is a monotonically increasing function of the buffer capacity. We analyze the buffer capacity determination problem with the objective of determining the minimum buffer capacity that achieves a desired production rate and also with the objective of maximizing the profit. It is shown that the computational performance depends on the rates of change among system states and not on the number of states at each stage and on the buffer capacity. Our numerical results show a significant computational improvement compared with using a discrete-event simulation. As a result, the mathematical programming approach is proposed as a viable alternative method for performance evaluation and optimization of continuous-flow systems with a finite buffer. [ABSTRACT FROM AUTHOR]

The optimal production control policy (i.e., the hedging point policy) for a single machine and single part-type manufacturing system for the case where the production surplus is accurately known has been reported in the literature. However, the production surplus is often observed inaccurately in practice. Ignoring this inaccuracy in using the optimal policy leads to not only non-robust situations but also high production costs. To consider the effect of the inaccurate observation, robustness of the production control policy is required. The robustness can be evaluated in terms of the difference between the production surplus trajectory under the policy with an inaccurate observation and the trajectory under the policy with an accurate production surplus (i.e., the hedging point policy). A difference of zero is the ideal case; however, this is generally impossible to achieve since the extent of the observation error is generally unknown. This article proposes a new robust production control policy that can give a small difference between the two trajectories. Compared with the hedging point policy, the proposed policy is more insensitive to production surplus inaccuracy in the neighborhood of the hedging point but responds more slowly to a failure of the machine. Simulation studies show that the proposed policy has a better robustness than the hedging point policy for cases where, just as in actual industrial practice, the machine failure time is much shorter than the up time of the machine. In these cases, with an increase in the observation error, the robustness of the proposed policy becomes increasingly better than that for the hedging point policy. [ABSTRACT FROM PUBLISHER]

Production cycle time is an important performance measure in manufacturing systems, and thus it is of interest to characterize distributional properties, such as quantiles, for informative decision making. This article proposes a non-linear quantile regression model for the relationship between stationary cycle time quantiles and corresponding throughput rates of a manufacturing system. The statistical properties of the estimated cycle time quantiles are investigated and the impact of dependent data from simulation output on parameter estimations is analyzed. Extensive numerical studies are presented to demonstrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

The performance of the batch-means procedure ASAP3 and the spectral procedure WASSP is evaluated on test problems with characteristics typical of practical applications of steady-state simulation analysis procedures. ASAP3 and WASSP are sequential procedures designed to produce a confidence-interval estimator for the mean response that satisfies user-specified half-length and coverage-probability requirements. ASAP3 is based on an inverse Cornish-Fisher expansion for the classical batch-means t -ratio, whereas WASSP is based on a wavelet estimator of the batch-means power spectrum. Regarding closeness of the empirical coverage probability and average half-length of the delivered confidence intervals to their respective nominal levels, both procedures compared favorably with the Law-Carson procedure and the original ASAP algorithm. Regarding the average sample sizes required for decreasing levels of maximum confidence-interval half-length, ASAP3 and WASSP exhibited reasonable efficiency in the test problems. [ABSTRACT FROM AUTHOR]

In a manufacturing enterprise, virtual environments can improve productivity by allowing employees to train without taking production equipment out of service. As a demonstration of this capability, we have developed a virtual environment to simulate overhead crane operation. This virtual environment was developed by combining 3-D factory drawings with 3-D simulation models of crane and load motion. The crane simulator allows an operator to maneuver a crane and load in three dimensions. Implemented on a PC with an update rate of 14.3 Hz, the simulator runs in real-time interaction that approximates live machinery. [ABSTRACT FROM AUTHOR]

A structured systems methodology was developed to analyse the problems of production interruptions occurring at random intervals in continuous process type manufacturing systems. At a macro level the methodology focuses on identifying suitable investment policies to reduce interruptions of a total manufacturing system that is a combination of several process plants. An interruption-tree-based simulation model was developed for macroanalysis. At a micro level the methodology focuses on finding the effects of alternative configurations of individual process plants on the overall system performance. A Markov simulation model was developed for microlevel analysis. The methodology was tested with an industry-specific application. [ABSTRACT FROM AUTHOR]

This article focuses on the use of an object-oriented approach in modeling integrated manufacturing systems. Solutions obtained through traditional modeling approaches at best give insight into a very narrow slice of the total system being modeled, and are valid only for the assumptions under which the model was built and executed. Analysts almost never track the actual performance of the system and compare actual results to those predicted by the model. There is a great need for a closed loop modeling operations environment, in which the model is regarded as an integral element of the decision/operations system. This could provide a foundation for achieving the long sought goal of organizational learning. Most developments in simulation languages may be classified into two categories such as graphical interfaces for input/output, and animation. Some of the more advanced languages employing graphical interfaces use artificial intelligence and expert systems concepts. They become application generators by interacting with the user to develop a set of code which can be passed directly to the base simulation language. Queuing network models have emerged as the most widely studied analytical models of manufacturing systems. Most network models used are of the Jackson-Gordon-Newell type.

Simulation modeling has been widely used to analyze complex stochastic systems, such as, to compute some performance measures of a modern manufacturing facility. Often, we are interested in optimizing these performance measures of the system with respect to some controllable parameters. Traditional methods to find an optimum of a simulation model usually require making a number of simulation runs, which can be computationally intensive. This study proposes a stochastic optimization method to optimize a simulation model in a single simulation run, with the potential of large savings in computational effort. Two algorithms based on this method are developed and evaluated empirically using an M/M/1 queue problem. Experimental results show that the algorithms, especially one of them, are promising and that this approach merits further investigation. [ABSTRACT FROM AUTHOR]