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This paper is being developed in Blazer on industrial engineering. In the last few decades, the global economy, in particular in international commerce and manufacturing organizations, has evolved substantially. The technical framework of today is thus distinguished by productivity-oriented, which can be accomplished by industrial engineering. This paper presents the different principles & approaches used in industrial engineering, such as time analysis, work studies, line balancing and the outcome of organizational disintegration tests in Blazer. This research has focused on several kinds of machinery to produce a Blazer. The traditional manufacturing industry has issues such as low efficiency, longer lead time, high rework & re-work, poor line balance, low style shift flexibility, etc. The implementation of Industrial Engineering correctly resolved these issues. This study looks at how to develop Blazer's processes by using Industrial Engineering, wasting less resources, time, raw materials, human capital and electricity.

Cast iron and steel weldments are the most common machine tool base elements. However, both construction methods have associated disadvantages for domestic machine tool manufacturers. This paper documents the investigation of an alternative method for machine tool base production using concrete to fill an additively manufactured polymer mold, where the motion components are attached to the concrete base after the initial concrete curing. Modal testing results for a three-axis, vertical spindle prototype indicate high damping and stiffness can be achieved using the concrete base construction. Advantages are reduced cost and lead time compared to traditional methods.

The continuous efforts are been put in by production engineers and process planning engineers to reduce or maintain minimum manufacturing lead time. The existing radial drilling machine took 184 s for grooving six-holes in the tie rod. The operator has produced the six grooves by repositioning the tie rod in the fixture. The total machining time required for completing one tie rod is 184 s out of which 138 s were machining time and the remaining 46 s was material handling time. In the present work design and fabrication of multi-spindle drilling, the head is fabricated to increase the production capacity of the manufacturing unit. The other merits of this design are quality and quantity products by minimizing operator fatigue. The methodology followed to accomplish the work included the concept development process and modeling. Design calculations and finite element analysis were carried out on the critical part such as gear and gear on the shaft for design validation. The unit was fabricated in-house and it was installed in the existing radial machine. The new machining time is 40 s out of which 30 s is machining time and 10 s was the machine handling time. This was achieved by the incorporation of the newly designed machine tool and the production rate was increased by 78%.

With the fourth industrial revolution on the verge of disruption, businesses and production companies around the world are trying to emulate the success of Toyota’s remarkable production system with a view of reducing waste and improving quality. Lean production has been the secret for Toyota to be as the most profitable automaker in the world. This paper presents a survey and reviews on how process improvement techniques such as the Lean Six Sigma (LSS) and KAIZEN may be implemented to realize reduced lead time in production processes and to attain the desired quality in concrete. The case study is based on the concrete production plant for the 750 MW (5 * 150 MW) Kafue Gorge Lower Hydro Power Project, which may be considered to have been one of the largest concrete batching plant with a total production capacity of 32 cubic meters. The analysis of the effectiveness and impact of the operation and management methods, i.e., LSS and KAIZEN techniques, were carried out over a period of approximately two years. Through literature review, evaluation of these philosophies was done by first defining waste in materials, time and work force at the concrete production plant. The KAIZEN, which is management techniques focusing on employees’ involvement to ensure continuous improvement and a high success rate of lean implementation at the plant, was applied and used thus creating a feedback kind of plant management technique review mechanism overtime. The complete implementation of the lean production system involves considerable organizational change while maintaining the true north. Furthermore, not only can these methods be used to realize Industrial Value Chain through lead time reduction and quality optimization of concrete but also provides applied management and economical improvements with assured reduced Takt-Time realization at the production plant.

In automated manufacturing systems, most of the manufacturing processes including machining are automated. Automatic tool change is one of the important parameters for reducing manufacturing lead time. Ceramic cutting tools are used to machine hard materials. Ti[C,N] mixed alumina ceramic cutting tools are widely used to machine hardened steel and Stainless Steel due to its superior mechanical properties. Martensitic stainless steel has wide applications in screws, bolts, nuts and other engineering applications. Machining studies on Martensitic Stainless Steel was conducted using Ti[C,N] mixed alumina ceramic cutting tool. Tool life was evaluated using flank wear criterion. The tool life obtained from experimental machining process was taken as training dataset and test dataset for machine learning. Using the dataset obtained from experimental machining tool life model has been developed using Gradient Descent algorithm. The model was validated using co-efficient of determination. The accuracy of the machine learning model was tested using the test data and 99.83% accuracy was obtained. Tool life model based on Gradient Descent Algorithm was successfully implemented for the tool life of Ti[C,N] mixed alumina ceramic cutting tool.Keywords: keyword 1; keyword 2; keyword 3 (List three to ten pertinent keywords specific to the article; yet reasonably common within the subject discipline.)

The problem that occurs in the packaging bottle production process is the amount of waste in it. Therefore, this study aims to make improvements in reducing waste of production time and provide recommendations for managing the production process so that in the future can be used as a reference in the production process optimization. The method used in this study is descriptive analysis conducted by examining the work and activities of an object. The results of the study show that in the production process, there was still a form of waste which, when viewed from the seven waste concept in the lean manufacturing system, there are some of the most dominant wastes such as inventory, waiting, process, overproduction, and defect. After improvement of the current mapping, the waste that occurs such as inventory, process, overproduction, waiting, and defects that occur in the production line reduced from the total lead time of 2.1 days with seven operators to 0.9 days with ten operators. Furthermore, the cycle time value of the current value stream mapping was 120.9 seconds, while the cycle time value of the proposed value stream mapping was 72 seconds. This shows an increase in productivity.

High quality solutions, performance and operational low cost are fundamental to a project success, in view of the fact that the current manufacturing philosophy is “producing more from less”. The purpose of this paper is to satisfy the requirements of an automotive industry building a project in quality of bushings concern that incorporate the vehicles combustion engines, particularly from industries. The method has na extensive experience in literary research about componentes eletromechanical-pneumatic constituents. The result was a reduction of a lead time enabling collision simulations and placement related to the increased productivity from 12 to 20 qualified components per minute. The conclusion is based on project’s essentiality to maintain the competitiveness of the company and maintenance of employments.

Globalization has dramatically changed the way in which products are produced by manufactures of all sizes. Small to medium sized organizations are now just as likely to engage in global outsourcing projects as large multinational teams (Tosse, 2005). Global distributed teams need to effectively communicate and collaborate throughout the entire product development process to produce innovative products of the highest quality in the shortest period of time. In industry, engineering change management (ECM) is recognized as a problem that receives too little attention relative to its importance. Wright’s (Wright, 1997) conclusion is that from the manufacturing perspective ECM is a disturbance obstructing smooth product manufacture, but such a perspective ignores ECM’s capacity to provide the incentive for product improvement. Wright’s conclusion is that a number of coordinated research programs are required to establish the ground rules for maximizing the product design benefits from EC activity. Many and especially late ECs are very costly for any development project. ECs consume one third to one half of the total engineering capacity and represent 20 to 50 % of total tool costs (Terwiesch & Loch, 1999). The key contributors to long EC lead times are: complex approval process, snowballing changes, scarce capacity and organizational issues. Loch (Loch & Terwiesch, 1999) analyzed the process of administering engineering chain orders within a large vehicle development project. Despite the tremendous time pressure in development projects, EC pr ocess lead times are in the order of several weeks, months and even over one year (Loch & Terwiesch, 1999). A detailed analysis has shown a low proportion of value-added time in the EC process – less than 8.5 %. An EC spends most of its lifetime waiting for further processing. Loch suggests the following improvement strategies in order to reduce EC lead time: flexible capacity, balanced workloads, merged tasks and sharing resources (pooling).

Manual work is the key source of skill and ingenuity in industrial manufacturing. At the same time, it is the most expensive resource factor. Often machines can replace humans for more effective manufacturing because machines outperform humans in terms of strength, precision and endurance. Humans, however, perform better than machines when flexibility and intelligence is required. Flexible Manufacturing Systems are capable of manufacturing wide variety of products with low volume size and minimal lead time. These manufacturing cells are usually equipped with high level computer based control and include highly flexible industrial robots also. Robots can partially resolve contradiction of flexibility and intelligence due to their more humanlike structure and programmability. To a large extent, robots have already relieved workers of many of the tedious, hard and unhealthy parts of industrial work. But the universal application of robots in small-batch highly customized production is hindered by the time consuming robot programming. This thesis shows efficient methods and processes for teaching and optimizing complex robot tasks by introducing cognitive robot programming, flexible robotics, and middleware. Intelligent user interfaces combining information from several sensors in the manufacturing system will provide the operator with direct knowledge on the state of the manufacturing operation. Thus, the operator will be able to determine the system state quicker. Sensory system calculates and proposes the optimal process settings. The key element is the new cognitive human-machine communication channels helping the operator to comprehend the information from the sensory systems. Novel middleware technology is facilitated for integration of elements from different system platforms into a coherent robot system and scaling it for different hardware complexity levels. The contributions of the thesis could be summarized as follows: 1. Introduction of a new scientific concept of task dependent, software component based controller for flexible manufacturing cells. 2. Development of a new paradigm of robot teaching and supervising, which opens a new dimension of robotization in the area of small and medium sized enterprises. 3. Introduction of a new concept for Coginitve Telemanipualtion.

This paper addresses a multi-period production/inventory problem with two suppliers, where demand sizes and supplier lead time are stochastic and correlated. A discrete time, single item inventory system is considered, where inventory levels are reviewed periodically and managed using a base-stock policy. At the end of each period, a replenishment order is placed, which enters a queue at the buffer stage and is consequently forwarded to the first available supplier. We present a mathematical model of this inventory system and determine optimal safety stock levels for it, in closed form, using matrix analytic techniques and the properties of phase type distributions. To account for the effect of order crossovers, which occur whenever replenishment orders do not arrive in the sequence in which they were placed, the inventory shortfall distribution is analyzed. Finally, a set of numerical experiments with a system with two suppliers is presented, where the proposed model is compared to other existing models.

Purpose The purpose of this paper is to investigate into the improvement strategies for lead time reduction of military aircraft major overhaul (enhance the overhaul task from present seven to nine-plus aircrafts as agreed to customer) for ABC Company. Design/methodology/approach This research has been conducted based on the available knowledge and extensive experience gained while working in the overhaul unit of the case organization for a long period of time. The research employs an integrated approach of multi-criteria decision method (in specific analytic hierarchy process (AHP)), theory of constraint (TOC) and simulation for M/M/1/K queuing environment for investigating the improvement strategies for lead time reduction in major overhaul of military aircraft. This has mainly included: Step 1: analysis of existing activity network using actual overhaul data; Step 2: ranking of constraint activities that most affects the lead time using AHP; Step 3: revised flow activity network using time buffers (TBs) concept of TOC; Step 4: mathematical model formulation for effective utilization of TB using single server finite queuing approach (M/M/1/K queuing environment); Step 5: discrete event simulation representing present overhaul conditions and revised overhaul conditions with different scenarios; and Step 6: sensitivity analysis and interpretation of results. The proposed methodology has been tested on an industrial case study dealing with an aircraft overhaul in India (namely ABC Company). Findings The proposed overhaul lead-time reduction plan points out the augmentation of resources in order to achieve more than 50 per cent reduction in lead time and waiting time under two scenarios – with overtime and without overtime. Research limitations/implications An integrated approach proposed has so far been applicable to the specific aircrafts (Jaguar/Mirage/Kiran) of the ABC Company overhaul division. However, the particular methodology can be proved potentially useful and highly practical when applying to other aircraft types. Originality/value The results indicate several problems with the current overhaul strategies that need focused process improvements and a need for capacity augmentation for achieving the enhanced overhaul task of nine+ aircrafts per year with reduced overhaul lead time. The proposed approach also provides the maintenance planners with a platform for decision analysis and support often ignored the capacity augmentation.

Remanufacturing is a viable way to prolong the useful life of an end-of-use product or its parts. Despite its economic, environmental, and social benefits, remanufacturing is associated with many challenges related to core (used product or its part) availability, timing and quality. The aim of this paper is to study how lean production could be used to tackle remanufacturing process challenges and contribute to shorter lead times. To meet this aim, we conducted a literature review and case studies of four remanufacturing companies. The case companies remanufacturing challenges were: (1) a lack of material requirements planning system, (2) poor core information, (3) a lack of core material, (4) poor spare parts information, (5) a lack of spare parts material, (6) insufficient quality management practices, (7) large inventories, (8) stochastic remanufacturing processes, (9) a lack of supply-demand balance, and (10) insufficient automation. These challenges contribute to long and variable remanufacturing process lead times. To tackle remanufacturing challenges, seven lean-based improvements with a major effect on improvements in lead time were suggested: standard operations, continuous flow, Kanban, teamwork, employee cross-training, layout for continuous flow, and supplier partnership. Providing that the suggested improvements are implemented, a possible lead time reduction of 83-99 per cent was projected. Funding Agencies|Swedish Governmental Agency for Innovation Systems [2013-03333]

In this study, the two-stage supply chain scheduling problem with multiple customers and multiple manufacturers is considered. The first stage consists of m manufacturers (suppliers), while the second stage contains q vehicles, each of which distributes the batches from the manufacturers to the customers. Multiple customers and average lead time are two most important issues in practice; however, no study has been carried out so far to investigate these two issues together for the two-stage supply chain scheduling problem. The main contribution of this study is to coordinate production and distribution decisions to obtain an effective scheduling in a two-stage supply chain that contains multiple customers and multiple manufacturers. A mixed integer linear optimization model is developed to formulate the problem with the average lead time objective. Because the problem has been shown to be NP-hard, a hybrid artificial bee colony and simulated annealing (HABCSA) algorithm is introduced and used to solve the problem. In addition, a lower bound (LB) and several structural properties for the problem are presented and different batching mechanisms are developed based on these properties. For the purpose of performance analysis of HABCSA with different batching mechanisms, detailed computational experiments are conducted using random instances which are generated based on real aluminum production data for different capacity levels. The experimental results indicate that the HABCSA heuristic consistently outperforms the Genetic Algorithm (GA) and the Artificial Bee Colony (ABC) algorithm for each capacity level.

Modular plant design is an approach for making chemical production more flexible and more efficient. Different approaches for modular plant design have been developed, for example in the CoPIRIDE or F3 factory project. They have in common, that lead time reductions for modular equipment are expected e.g. by utilizing design repetition or parallelization of preassembly of modules. To support the decision for or against a modular concept, besides cost effects possible lead time changes compared to conventional concepts should be anticipated in early economic evaluations already. In this article, a lead time estimation method will be presented that correlates project costs and project durations and can be applied to modular and non-modular plants enabling comparative studies. An example from a previous paper was used to investigate the impact of modularization on lead time. It includes modular production lines and a non-modular backbone facility that provides energy and utility supply. A range of investment sizes (FCI of 3–95 mio. €) was investigated and compared with a conventional reference plant. Total lead time reduction was in the range from 2.6 to 5.5 month depending on investment size. For a more significant impact on the lead time the modularization approach needs to be modified by also applying modular design to the backbone facility. In this case depending on investment size total lead time reduction would be between 3.9 and 18.7 months representing a very significant reduction of 23%–60% compared to the lead time of the conventionally designed reference plant. This is considered as the maximum expectable lead time reduction that can be achieved through modular plant design. This reduction would represent a major potential for speeding up construction of chemical plants.

This paper aims at detecting online cognitive failures in driving by decoding the electroencephalography (EEG) signals acquired during visual alertness, motor planning and motor-execution phases of the driver. Visual alertness of the driver is detected by classifying the preprocessed EEG signals obtained from his prefrontal and frontal lobes into two classes: alert and nonalert. Motor planning performed by the driver using the preprocessed parietal signals is classified into four classes: braking, acceleration, steering control, and no operation. Cognitive failures in motor planning are determined by comparing the classified motor-planning class of the driver with the ground truth class obtained from the copilot through a hand-held rotary switch. Lastly, failure in motor execution is detected, when the time delay between the onset of motor imagination and the electromyogram response exceeds a predefined duration. The most important aspect of the present research lies in cognitive failure classification during the planning phase. The complexity in subjective plan classification arises due to possible overlap of signal features involved in braking, acceleration, and steering control. A specialized interval/general type-2 fuzzy set induced neural classifier is employed to eliminate the uncertainty in classification of motor planning. Experiments undertaken reveal that the proposed neuro-fuzzy classifier outperforms traditional techniques in presence of external disturbances to the driver. Decoding of visual alertness and motor execution are performed with kernelized support vector machine classifiers. An analysis reveals that at a driving speed of 64 km/h, the lead time is more than 600 ms, which offer a safe distance of 10.66 m.

Just-in-time manufacturing is a main manufacturing strategy used to enhance manufacturers’ competitiveness through inventory and lead time reduction. Implementing just-in-time manufacturing has a number of challenges, for example, effective, frequent and real-time information sharing and communication between different functional departments, responsive action for adjusting the production plan against the continually changing manufacturing situation. Internet of Things technology has the potential to be used for capturing desired data and information from production environment in real time, and the collected data and information can be used for adjusting production schedules corresponding to the changing production environment. This article presents an Internet of Things based framework to support responsive production planning and scheduling in just-in-time manufacturing. The challenges of implementing just-in-time manufacturing are identified first and then an Internet of Things based solution is proposed to address these challenges. A framework to realise the proposed Internet of Things solution is developed and its implementation plan is suggested based on a case study on automotive harness parts manufacturing. This research contributes knowledge to the field of just-in-time manufacturing by incorporating the Internet-of-Things technology to improve the connectivity of production chains and responsive production scheduling capability.

Large-scale battery energy storage systems (BESS) have become increasingly interesting to provide ancillary services for the electricity grid. Especially the German frequency containment reserve (FCR) market which is organized by the German transmission system operators (TSO) is attractive for BESS. Because of its importance for the system stability, FCR has to be provided continuously with 100% availability. Due to the limited energy capacity of BESS, an operating strategy is required to enable continuous FCR provision. The German TSOs have defined several requirements that BESS have to comply with as well as degrees of freedom (DoF) to enable corrective measures such as selective recharging for an operating strategy. This paper presents a sensitivity analysis of different operational parameters based on an operating strategy developed within the M5BAT (Modular Multi_Megawatt Multi-Technology Medium-Voltage Battery Energy Storage System) project. Within this project the construction and operation of a 5 MW hybrid BESS with five different battery technologies is realized. As this BESS will mainly be operated in the German FCR market, it is used as reference for this paper. The developed operating strategy considers the TSO’s FCR requirements and DoF and is fully applicable to the German FCR market. Within this paper it is explained how corrective measures have to be triggered in order to comply with the requirements. A model of the M5BAT BESS, which comprises various battery technologies and an energy management system (EMS) for load allocation among multiple battery strings, is introduced. Simulations of FCR operation with measured frequency data of the year 2014 are presented. The influence of the lead time and duration of corrective measures, the EMS and the FCR requirements on compliance with the FCR requirements, amount of corrective measures, resulting energy throughput, state-of-energy (SOE) distributions and cycle numbers are investigated. The results show a significant impact of all parameters. It is found that velocity and flexibility of corrective measures (e.g. recharging) and an efficient EMS are prerequisites for FCR operation with BESS under the applicable regulation. Additionally, the results indicate that the overall benefits of FCR provision with BESS could be improved with an adjustment of the requirements (30-min-criterion).

Productivity achievement at PT Adi Satria Abadi (Golf Gloves Division) is not optimal because ofthe waste. Value Stream Mapping as a Lean Manufacturing tool is used to map the production processand identify and eliminate the waste. The advantage of VSM is its capability to give visual map of valueadded flow process, necessary but non value added flow process, and non value added flow process. In thisstudy Waste Assessment Model (WAM) also have been implemented to identify the waste. The sequence ofthree greatest waste are Defect/Reject 24,73%, Unneccessary Inventory 18,80%, and Unneccessary Motion15,44%. This study can reduce production lead time 62,22 minutes and improve the production throughputby 77 pcs.

Introduction 3D printing seems to have more and more applications in maxillofacial surgery (MFS), particularly since the release on the market of general use 3D printers several years ago. The aim of our study was to answer 4 questions: 1. Who uses 3D printing in MFS and is it routine or not? 2. What are the main clinical indications for 3D printing in MFS and what are the kinds of objects that are used? 3. Are these objects printed by an official medical device (MD) manufacturer or made directly within the department or the lab? 4. What are the advantages and drawbacks? Methodology Two bibliographic researches were conducted on January the 1st, 2017 in PubMed, without time limitation, using “maxillofacial surgery” AND “3D printing” for the first and for the second “maxillofacial surgery” AND “computer-aided design” AND “computer-aided manufacturing” as keywords. Articles in English or French dealing with human clinical use of 3D printing were selected. Publication date, nationality of the authors, number of patients treated, clinical indication(s), type of printed object(s), type of printing (lab/hospital-made or professional/industry) and advantages/drawbacks were recorded. Results Two hundred and ninety-seven articles from 35 countries met the criteria. The most represented country was the People's Republic of China (16% of the articles). A total of 2889 patients (10 per article on average) benefited from 3D printed objects. The most frequent clinical indications were dental implant surgery and mandibular reconstruction. The most frequently printed objects were surgical guides and anatomic models. Forty-five percent of the prints were professional. The main advantages were improvement in precision and reduction of surgical time. The main disadvantages were the cost of the objects and the manufacturing period when printed by the industry. Discussion The arrival on the market of low-cost printers has increased the use of 3D printing in MFS. Anatomic models are not considered to be MDs and do not have to follow any regulation. Nowadays, they are easily printed with low-cost printers. They allow for better preoperative planning and training for the procedures and for pre-shaping of plates. Occlusal splints and surgical guides are intended for the smooth transfer of planning to the operating room. They are considered to be MDs and even if they are easy to print, they have to follow the regulations applying to MDs. Patient specific implants (custom-made plates and skeletal reconstruction modules) are much more demanding objects and their manufacturing remains nowadays in the hands of the industry. The main limitation of in-hospital 3D printing is the restrictive regulations applying to MDs. The main limitations of professional 3D printing are the cost and the lead time. 3D printed objects are nowadays easily available in MFS. However, they will never replace a surgeon's skill and should only be considered as useful tools.

In this work, we examine a single stage, periodic review inventory system where two modes, namely regular mode and expediting mode are available for a firm to obtain its replenishment. The firm can choose expediting mode with shorter lead time at a higher cost when necessary. A two-replenishment-mode model, with random expediting points is established and an innovative ordering policy (S, e) which replenishes the inventory level to S in every cycle and expedites a part of the order using fast mode when the inventory level drops to or below a certain level e, is proposed. A simulation-based optimization approach is employed to solve the problem. To be specific, an infinitesimal perturbation analysis (IPA) method is applied to estimate the gradients of the objective function and a gradient search algorithm is then used to find the best (S, e). Numerical experiments have validated the IPA estimate of (S, e) and shown that our new (S, e) policy outperforms the pure order-up-to policy and two single review moment policies. Sensitivity analysis has been conducted to evaluate the impact of system parameters of interest and managerial insights have been drawn.

The article of record as published may be found at http://dx.doi.org/10.1016/j.apenergy.2017.05.068 Hybrid microgrids that use renewable energy sources can improve energy security and islanding time while reducing costs. One potential beneficiary of these systems is the U.S. military, which can seek to improve energy security when operating in isolated areas by using a microgrid rather than relying on a fragile (or nonexistent) commercial network. Renewable energy sources can be intermittent and unpredictable, making it difficult to plan operations of a microgrid. We describe a scenario-robust mixedinteger linear program designed to utilize ensemble weather forecasts to improve the performance of a hybrid microgrid containing both renewable and traditional power sources. We exercise our model to quantify the benefit of using ensemble weather forecasts, and we predict the optimal performance of a hypothetical grid containing wind turbines by using simulated realistic weather forecast scenarios based on data. Because forecast quality degrades with lead time, we perform a sensitivity analysis to determine which planning horizon results in the best performance. Our results show that, for dayahead planning, longer planning horizons outperform shorter planning horizons in terms of cost of operations, but this improvement diminishes as the planning horizon lengthens. Office of Naval Research

This paper attempts to propose a new multi-stage production-inventory system with and without lead times via an optimal control model. The proposed optimal control model for lead times contains some delays in the state variables. The considered dynamical system is a multi-stage production-inventory one which obeys a linear quadratic optimal control model with time delays in the states. Production lead times can be considered as required time for production. In the proposed system, the inventories of stocks are considered as state variables while the demand and ordering levels are control variables. In the proposed multi-stage system, returned items from one stock to the previous one is allowed with recycling. The exact solution of non-delay model along with the approximate solution of delayed system are obtained and compared in a real case study in granular polymer industry which the products are 3D panels and expanded polystyrene (EPS) blocks.

The current scenario of high competition makes companies look increasingly optimized processes, with the least possible losses and the ultimate in quality and productivity. Industrial layout plays an important role in this context, given that the physical layout of machinery, equipment, circulation areas, storage areas and people directly influences the efficiency of an operation. In the midst of this need for constant improvement, lean production emerged, which has proven to be an efficient method for companies to improve their performance. This study aims to define a layout that allows the optimization of business processes, based on the principles of lean production. The development of this research was carried out by the method of action research where analysis tools were used to diagnose the current situation and, thereafter, for the formulation of the proposed improvement. The results showed that the changes proposed in the layout are able to reduce the company's lead time by 46%, eliminate losses, improve the organization of productive sectors, and ensure agility in the manufacturing process.

Modularity has shown great potential in the manufacturing industry, reducing order lead time and creating variety with limited resources. In the construction industry, the implementation of modular...

Remanufacturing planning issues involve extremely complex strategic decisions within the supply chain system, especially considering the multiple products and joint components that are involved. It is very important to know how to determine the appropriate amounts of procurement quantity and lot size. In actual lot-sizing production-to-order problems for recoverable remanufacturing systems, input data or parameters are often imprecise or fuzzy. This work develops a fuzzy multi-objective linear programming (FMOLP) model that simultaneously minimizes total costs, lead time and CO 2 emissions with reference to multiple products and joint components. The proposed model evaluates cost-effectiveness, lead time and CO 2 emissions, while integrating multi-products, multi-suppliers, multi-components, joint components and multi-machines into one remanufacturing production system. The analytical results presented in this work are able to assist decision-making managers to better understand systematic analyses, and the potential for cost-effectiveness, lead time and CO 2 emissions in recoverable remanufacturing planning.

In the present competitive and demanding business markets, manufacturing industries need to improve their strength and must concentrate on their process flows by assigning the task resources carefully to improve productivity. It also focuses on continuous improvements with the total involvement of all employees with optimum utilisation of man power and machine by reducing idle time and lead time. They also provide the application for variety of tools and strategies which can help in identification of waste reduction or elimination of waste, lowering the product cost, reducing human effort and minimising product manufacturing time. In the current competitive business era, an industry unable to sustain in the global business without implementing the computer integrated manufacturing in the manufacturing environment. In order to overcome, a computer-based lean audit methodology is to be implemented in the production environment for improving the production characteristics like quality, reduce wastage and red...

Changes in requirements may result in the increasing of product development project cost and lead time, therefore, it is important to understand how requirement changes propagate in the design of complex product systems and be able to select best options to guide design. Currently, a most approach for design change is lack of take the multi-disciplinary coupling relationships and the number of parameters into account integrally. A new design change model is presented to systematically analyze and search change propagation paths. Firstly, a PDS-Behavior-Structure-based design change model is established to describe requirement changes causing the design change propagation in behavior and structure domains. Secondly, a multi-disciplinary oriented behavior matrix is utilized to support change propagation analysis of complex product systems, and the interaction relationships of the matrix elements are used to obtain an initial set of change paths. Finally, a rough set-based propagation space reducing tool is developed to assist in narrowing change propagation paths by computing the importance of the design change parameters. The proposed new design change model and its associated tools have been demonstrated by the scheduling change propagation paths of high speed train’s bogie to show its feasibility and effectiveness. This model is not only supportive to response quickly to diversified market requirements, but also helpful to satisfy customer requirements and reduce product development lead time. The proposed new design change model can be applied in a wide range of engineering systems design with improved efficiency.

The emergence of Additive Manufacturing (AM) technologies brings in the reduction of material consumption in terms of avoiding the repeated fabrication of dies as well as comparatively high material efficiency. However, despite of widespread application and evident advantages over conventional manufacturing techniques, AM still suffers from long lead time and redundant material usage when fabricating large-volume solid objects. This fact would definitely restrict the diffusion of AM technology. Based on this, a design strategy is proposed in this paper from the perspective of process planning focusing on the material consumption in additive manufacturing of relatively large-volume solid parts. Instead of processing the digital models directly, the sliced data of digital models is adopted for the design and optimization, and finally outputting the paths driving the AM machine to realize the practical fabrication. The sliced contours of the model are obtained based on a given layer thickness at first. Subsequently, the areas to be filled on each layer are determined according to the input contours and the self-supporting capability of the material. The interior regions confined by the generated internal contours do not need to be filled necessarily because they have no effect on the parts’ geometry and the materials can be saved accordingly. At last, a skeleton-based path planning method is utilized to address the long and narrow geometry to improve the deposition performance and surface quality. Several tests are used to verify the proposed strategy and the results show its effectiveness and feasibility in reducing the material consumption, enabling AM to be a more environmental friendly and sustainable manufacturing method.

This study proposes a method of interactive plant simulation modeling which delivers the online simulated results to the field operators and induces them to take proper actions in the case of pre-identified accident scenarios in a chemical plant. The developed model integrates the real-time process dynamic simulation with 3D-CFD accident simulation in a designed interface using object linking and embedding technology so that it can convey to trainees the online information of the accident which is not available in existing operator training systems. The model encompasses the whole process of data transfer till the end of the training at which a trainee operates an emergency shutdown system in a programmed model. In this work, an overall scenario is simulated which is from an abnormal increase in the main valve discharge (second) pressure due to valve malfunction to accidental gas release through the crack of a pressure recorder, and the magnitude of the accident with respect to the lead time of each trainee’s emergency response is analyzed. The model can improve the effectiveness of the operator training system through interactively linking the trainee actions with the simulation model resulting in different accident scenarios with respect to each trainee’s competence when facing an accident.

We review the literature spanning 60 years of efforts to model the phenomenon of order crossover. The importance of this research has increased due to today's longer ocean supply chains, with their greater inherent uncertainty. The incidence of order crossover is higher in these supply chains, and ignoring it will result in overestimation of safety stock. The literature is grouped into four areas, which are described separately, and is mapped to reveal gaps. Gaps exist for combinations of lead time distributions, demand distributions, and inventory policies where extant methods do not address order crossover. The effective lead time approach has proven flexible enough to be used in a wide range of periodic review situations. However, our results show that its accuracy is undermined by bimodal skewed lead-time distributions, especially when lower bounds are nonzero. Future research needs to concentrate on exploring nonparametric methods or similar methods robust to different lead time distribution assumptions to provide a method of setting safety stock in “real world” situations where orders cross.

This paper deals with the simulation study carried out to solve bottleneck operations using manufacturing process reengineering. The study was carried out in a ceramic fiber products manufacturing company that deals with heat insulation solutions. The study mainly concentrates on the current capacity of facilities and delay in the manufacturing lead time in order to meet the order fulfillment lead time (OFLT). A simulation model was developed for the current scenario, and all the necessary performance measures were analyzed in order to propose changes in the process. It was found that the facilities had huge cycle time to process the products to the next stage, which created huge delays in meeting the OFLT. The outcome of the simulation was taken into account by the decision makers and recommendations implemented for the retro fitment of existing facilities. Using process reengineering, the proposed changes in the manufacturing line yielded 50% reduction in cycle time and manufacturing lead time (MLT) was reduced to 1.5 from 3 days.

Quality measurement is the trigger for quality improvement; things that cannot be measured therefore can be improved. The result of poor quality in the house hold construction projects in the Western Cape hence might be the lack of quality measurement methods or standards. The research intended to provide clients, building inspectors, building inspectors, project managers, designers and contractors with the necessary information needed to better manage the quality of house hold construction projects in the Western Cape Province. Factors that affect the quality of house hold construction projects during the construction phase were identified. The use of hybrid was implemented in order to exhaust all possible ways to obtain data and questionnaires were developed and used as research tools to obtain the opinions of respondents that included the contractors, building inspectors, household and project managers, on the factors affecting construction projects and how these factors can methodology be addressed to ensure the construction of quality buildings. It was concluded that the most important factors affecting the quality of house hold constructions projects are, the skills and experience of contractors and project managers, site lay-outs, materials, equipment used, Mediterranean weather conditions, lead time in decision making. Therefore the authors recommend that the construction industry should have a stand-alone board that deals with quality standards and controls the quality standards of buildings by taking into considerations the factors identified and also this board should behavior have rights to demolish buildings that are not up to standard. Article DOI: http://dx.doi.org/10.20319/mijst.2016.s11.195211 This work is licensed under the Creative Commons Attribution-Non-commercial 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.

As a key to improve the performance of the interbay automated material handling system (AMHS) in 300 mm semiconductor wafer fabrication system, the real-time overhead hoist transport (OHT) dispatching problem has received much attention. This problem is first formulated as a special form of assignment problem and it is proved that more than one solution will be obtained by Hungarian algorithm simultaneously. Through proposing and strictly proving two propositions related to the characteristics of these solutions, a modified Hungarian algorithm is designed to distinguish these solutions. Finally, a new real-time OHT dispatching method is carefully designed by implementing the solution obtained by the modified Hungarian algorithm. The experimental results of discrete event simulations show that, compared with conventional Hungarian algorithm dispatching method, the proposed dispatching method that chooses the solution with the maximum variance respectively reduces on average 4 s of the average waiting time and average lead time of wafer lots, and its performance is rather stable in multiple different scenarios of the interbay AMHS with different quantities of shortcuts. This research provides an efficient real-time OHT dispatching mechanism for the interbay AMHS with shortcuts and bypasses.

This article proposes an integrated product-service model to ensure the system availability by concurrently allocating reliability, redundancy, and spare parts for a variable fleet. In the literature, reliability and inventory allocation models are often developed based on a static installed base. The decision becomes really challenging during new product introduction, as the demand for spare parts is nonstationary due to the fleet expansion. Under the system availability criteria, our objective is to minimize the fleet costs associated with design, manufacturing, and after-sales support. We tackle this reliability--inventory allocation problem in two steps. First, to accommodate the fleet growth effects, the nonstationary spare parts demand stream is modeled as a sum of randomly delayed renewal processes. When the component's failure time is exponential, the mean and variance of the lead time inventory demand are explicitly derived. Second, we propose an adaptive base stock policy against the tim...

Additive manufacturing (AM) has become popular for both industrial and personal use thanks to the freedom and benefits it provides in designing parts, reducing lead time, improving inventory, and part consolidation. However, few studies examine process planning issues in a network of AM systems that account for part-to-printer assignment involving multiple parts and printers with scheduling objectives. AM printers are characterized by different processes, heating technologies, and sizes of the build chamber, which impacts efficient and effective process planning and 3D printer scheduling. Given fixed, unrotated orientation of parts, we propose a decision aiding model based on a multi-objective optimization for a batch of parts and multiple printers. The proposed model considers operating cost, load balance among printers, total tardiness, and total number of unprinted parts as objectives in fused deposition modeling (FDM) process. A case study with automotive parts is used to verify and validate model functionalities. Then, the conflicting objectives of the model are analyzed using trade-off analysis to understand conflicting aspect among objectives. Next, a designed experiment with different number of parts and printers show the complexity and the generalization of the model.

Rapid growth of renewable energy sources (RES) in the generation capacity mix poses substantial challenges on the operation of power systems in various time scales. Particularly in the intra-hour time scale, the interplay among variability and uncertainty of RES, unexpected transmission/generation outages, and short dispatch lead time cause difficulties in generation-load balancing. This paper proposes a method to quantify the intra-hour flexibility region. A robust security-constrained multiperiod optimal power flow model is first constructed to quantify the frequency, magnitude, and intensity of insufficient flexibility. The randomness of RES is captured by uncertainty sets in this model. The N-k contingency, spinning reserve, and corrective control limit constraints are included. This model is then cast into a two-stage robust optimization model and solved by the column-and-constraint generation method. The emergency measures with a least number of affected buses are derived and subsequently assessed by the postoptimization sensitivity analysis. Finally, the operational flexibility region is determined by continuous perturbation on the RES penetration level and the forecast error. The IEEE 14-bus system and a realistic Chinese 157-bus system are used to demonstrate the proposed method.

Material Management has always been a major challenge in the world of industry, especially the world of gas transportation. Poor on material planning, limitationon material supply the length of lead time delivery of materials is often a major constraint on the operational productivity. The obligation to maintain the reliability of the instrument to ensure smooth gas supply to consumers remains to be one of the challenges in maintaining productivity. These efforts will not be successful if the company is not able to increase the flexibility of the material supply chain. Not Providing Information Regarding Details Material stock, remoteness Distance Between warehouse and Station, Not Providing Information Details on stock Material, remoteness Distance Between warehouse and Station, and manual data collection worsen the problem tha couldt cause the error on calculating material stock, moreover the problem become more complicated by the lack of collaboration of material information that should be known by the user as the material user on field and planners as a warehouse supervisor. One solution to the problem is to develop the Material Traceabillity Strategy- A technology that can replace manual data entry process that still use paper as a recording media, allows personnel to track and manage the material in real time, Improve Information Sharing among divisions. This paper will discuss the problems and solutions that are applied in order to improve the reliability of materials that can improve supply chain collaboration in the handling of the material. This paper emphasizes the importance of the revolution in material handling in oil & gas transportation company that has been applied and proved successful in PT. Pertamina Gas Eastern Java Operation Area.

We develop a team based labour assignment methodology for NPD projects.Proposed hierarchical methodology integrates VSM, DSM and clustering techniques.The aim is to eliminate waste and create flow to reduce lead time.A real life application is performed to evaluate the proposed methodology.The results tested by simulation have promised significant lead time reduction. This study explores the organizational aspects of new product development projects and proposes a new team-based labour assignment methodology. The proposed hierarchical methodology focusses on the project value stream and aims to shorten lead time through waste reduction. Lean product development tools, such as clustering and design structure matrix tools, are integrated with the methodology. A detailed real-life case study is presented and the proposed methodology is evaluated using discrete event simulation. Experiment results show that the proposed methodology and team-based structure provide superior lead time performance when compared to conventional organizational setting. This study contributes to existing literature by presenting evidence of the effect of teams on NPD lead time performance.

This paper investigates the challenges of railway traffic controllers in dealing with big disruptions and the kind of support tools that could help to improve their task in terms of performance, lead time and workload. The disruption handling process can be partitioned into three phases resembling a bathtub. For each phase the essential decision making process has been identified. Currently, the support to rail traffic controllers in case of severe disruptions is limited to predefined contingency plans that are not always feasible or applicable. In the literature, models and algorithms have been identified that could be used in the different parts of the three phases of the disruption handling process. This paper investigates the processes of disruption management in practice and the challenges that traffic controllers are facing during a disruption. The literature of models applicable to disruption management is reviewed and classified based on the three phases of the traffic state during disruptions. Finally, a rescheduling optimization model is applied to a case of complete blockage on a corridor of the Dutch railway network. The case study shows how a microscopic model could support the traffic controllers by providing real-time solutions for different phases of a disruption.

The design of casting components is a complex activity, which is usually based on guidelines scattered in the literature, or based on the designer’s accumulated experience. A single failure in the casting process selection can increase design and production time and, in critical cases, result in a collapse of the manufacturing and assembly of components. Nowadays the selection is made by prioritizing the features of the casting process, but this action could be carried out during the product development stage, assisting the designer. This could allow the project to adjust to a more viable casting process. In this context, our goal is to propose a selector for casting processes to be used during the early stages of the embodiment design. It was achieved through the use of quality function deployment and design for manufacturing (DFM) principles. Our proposal relates the component’s main functions with each process characteristic (mass, minimum section thickness, draft angle, surface finish, dimensional tolerances, minimum lot and lead time) through a correlation matrix, resulting in importance indexes for these characteristics. Furthermore, the importance indices obtained are related to the capability of each casting process discussed, providing a process rating. A checklist based on DFM principles is also provided to guide the designer when a need for improvement is observed or no processes are suited for producing the desired part. For validation, two ferrous and two nonferrous cast parts were analyzed. The results were compared with other selectors described in the literature and with processes actually used in the industry. Thus, they have shown a good relation with the other methods, especially regarding the quantitative classification determined by the proposed selector.

To maintain a multi-stage cleaner production process, the major task is eliminating all defective items during the production system and an investment is necessary to reduce the probability of in-control state to out-of-control state of machinery system. In this direction, a logarithmic expression suggested by Porteus (1986) to consider in a single-stage imperfect manufacturing process for quality improvement, whereas this paper enables to consider the similar investment in a complex multi-stage imperfect manufacturing process to clean the production system. Using it, this paper develops a joint replenishment problem for complex multi-stage quality improvement. The study investigates a stochastic inventory model with a budget constraint for simultaneously optimizing number of shipments, replenishment interval, safety factor, backorder discounts, quality factor, and lead time as decision variables. Lead time is assumed as stochastic in nature, where a lead time crashing cost is used to reduce the lead time. As lead time is stochastic, a backorder price discount is allowed to save lost sells. To solve this problem, an improved algorithm is developed and two theorems are proved to obtain global optimal solution for this model analytically. Finally, some numerical examples and graphical illustrations are given to illustrate this model.

Additive manufacturing technology has been evolving for several years. New material options, better processing speeds and greater autonomy are some of the characteristics of this technology that are still under research. However, in its current state, many commercially available 3D printers are competing with traditional manufacturing techniques in the fabrication of end-use products. In this paper, different additive manufacturing technologies are compared with injection moulding in a real-world case study. The comparison is conducted in terms of lead time and total production cost. From the case under study, it becomes obvious that none of the additive manufacturing technologies examined is yet able to practically replace injection moulding for medium- and high production volumes. However, when considering low-volume production, both rapid tooling and additive manufacturing may offer an alternative that could result into shorter lead times and decreased total production costs. In addition, the introduct...

Aerospace industry is well known to be one of the most demanding sectors to work with. It is strongly normalized, monitored and audited on behalf of airworthiness. In this scenario, continuous improvement is a must, to comply not only with requirements, but also lead times and costs. TITANIA, one of most recognized materials testing labs in the world working for aerospace, moved to a tailor-made integral management system to deal with the high volume of data they deliver to their customers. After a two years effort, now is exploiting its results by offering better lead time compliances, more reliable test reports and new data analysis services. Digital transformation has pushed TITANIA into Industry 4.0. This paper presents the followed methodology and the first results obtained.

Deep drawing process is mainly used to produce automotive & aerospace components, house hold utensils, casings of electronic devices and many more. It is a plastic deformation process consists of tools viz. punch, die and blank holder. The workpiece is set on the die and hold with blank holder. Then, punch travel to deform the workpiece. The tooling of the process varies with different material and geometrical aspects. The die of the deep drawing process plays a vital role because the precision and accuracy of final product is depending upon the accuracy, surface quality and tolerance of the die. The die designing for any component is a combination of art, science and expertise. Of course, it is also tedious job and that requires highly skilled man power. Hence, an expert system has been developed to design die for multi stage deep drawing operations using VB.NET and AUTOCAD. Multi stage deep drawing process (MSDDP) is normally used for the components having high length to diameter ratio (LDR). This system is indigenous of its kind which requires few data i.e. work material type, physical properties & shape and size of final product. The system will predict and estimate number of draws, clearance and force required by punch & blank holder during each pass. The knowledge of die design experts (industries, academics and professionals) are fed in terms of rules. The system is quite capable to generate manufacturing drawing of die sets for all sequence of operations. Moreover, it is most suitable to make templates of products which are normally used during inspection and testing. This will reduce indirect costs and lead time. It also improves quality and productivity.

The chemical and biochemical industry has to face the challenges of globalization, short product cycle times and volatile markets. Therefore, the lead time of development projects has to be shortened. Modules and module-based plant design are widely discussed to enable shorter time-to-market by reuse of engineering effort and standardization. In this paper general requirements on modules in process engineering and modules for particular applications in the chemical and biochemical industry are reviewed. This includes the impact of modules on the planning process and examples of realized modular equipment concepts. Based on this, a general terminology definition of ‘modules’ and of specific module types for the process industry is presented, whereas modules on various ‘aggregation levels’ are accounted. A ‘block representation frame’ stores information and tracks information fluxes along the whole process and plant life cycle and on different ‘realization levels’ from laboratory studies over miniplant validation to production plant design and operation.

The foundry industry provides near net shape metal casting for a wide range of industries, producing components in ferrous and non-ferrous metal castings in a range of sizes from miniature items as small as zips to large castings such as ships' propellers.\ud \ud The sand casting process has changed little over centuries, except for incremental improvement in materials and mechanisation of the process, the fundamental process being that of sand compacted around a pre-manufactured mould pattern which is then removed to cast the metal. For mass production stage this is both efficient and economical, however during development and prototyping production stages the requirement for mould production tooling, the design constrained production method means this stage is often a major bottleneck in new product development.\ud \ud Additive manufacturing has been used to manufacture sand moulds for metal sand casting using laser sintering and sand bonding process without the need for tooling. This research focuses on optimisation of the build parameters for additive manufactured sand print bonded mould tools specifically for automotive aluminium castings.\ud \ud The approach taken in this research is to evaluate characteristics of casting produced and relates to the permeability, dimensional accuracy, tensile and compressive crush strength, density, impact strength and high temperature resistance of the mould tool produced. These properties are required to compare the 3D Sand Printing (3DSP) process to traditional Furan based casting sand mixtures. The automotive turbo charger casing was used to validate the build parameters optimisation process.\ud \ud This research would be of interest to designers and manufacturing engineers wishing to take advantage of the implications of having new design freedom, tool-less manufacturing with short lead times in a wide range of materials using fundamentally tried and tested foundry industry casting techniques. This research has demonstrated 3DSP process has the capability to manufacture sand patterns to permeability, accuracy, tensile and compressive strength comparable to traditional sand casting process.

European countries actually adopt industry 4.0 and supply chain 4.0 philosophy. Enterprise modelling methodologies define enterprise as a system, which can integrate new technologies, Internet of things, automation and robotics in collaboration with people. GRAI methodology and its supporting tool GRAIMOD are used for modelling, analysing and improving enterprise supply chain performance. QCD (quality, cost and lead time) criteria are combined (in GRAIMOD) to social, societal and environmental dimensions for improving the company supply chain. This paper presents how lead-time criterion could be implemented for increasing supply chain performance. A real application is given for illustrating the concepts presented.

Clients expect a short lead-time from aircraft maintenance services. In order to minimize the lead time, it is vital to analyse service processes related to maintenance tasks and identify existing problems such as bottleneck tasks and wastes related to different tasks. The main purpose of the manuscript is to demonstrate the use of the VSM-based (value stream mapping) methodology together with other tools, which were used in aircraft maintenance processes in minimizing the lead-time of maintenance services and, subsequently, minimizing the costs of maintenance services. The manuscript illustrates the use of VSM in enhancing the process cycle efficiency (PCE) of maintenance services provided in an aircraft maintenance services providing firm (AMSPF).

It is vital for make-to-order manufacturers to shorten the lead time to meet the customers’ requirements. Holding work-in-process (WIP) inventory at more stations can reduce the lead time, but it also brings about higher inventory holding cost. Therefore, it is important to seek out the optimal set of stations to hold WIP inventory to minimize the total inventory holding cost, while meeting the required due date for the final product at the same time. Since the problem with deterministic processing times at the stations has been addressed, as a natural extension, in this study, we address the problem with stochastic processing times, which is more realistic in the manufacturing environment. Assuming that the processing times follow normal distributions, we propose a solution procedure using genetic algorithm.