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The definition of cycle time is the time from the wafer start to the wafer output. It usually takes one or two months to get the product since customer decides to produce it. The cycle time is a critical factor for customer satisfaction because it represents the response time to the market. Long cycle time reflects the ineffective investment for the capital. The cycle time is very important for foundry because long cycle time will cause customer unsatisfied and the order loss. Consequently, all of the foundries put lots of human source in the cycle time improvement. Usually, we make decisions based on the experience in the cycle time management. We have no mechanism or theory for cycle time management. We do work‐in‐process (WIP) management based on turn rate and standard WIP (STD WIP) set by experiences. But the experience didn’t mean the optimal solution, when the situation changed, the cycle time or the standard WIP will also be changed. The experience will not always be applicable. If we only have the experience and no mechanism, management will not be work out. After interview several foundry fab managers, all of the fab can’t reflect the situation. That is, all of them will have an impact period after product mix or utilization varied. In this study, we want to develop a formula for standard WIP and use statistical process control (SPC) concept to set WIP upper/lower limit level. When WIP exceed the limit level, it will trigger action plans to compensate WIP Profile. If WIP Profile balances, we don’t need too much WIP. So WIP level could be reduced and cycle time also could be reduced.

Facing keen worldwide competition, it is not enough for companies to pursue customer satisfaction; they must actively pursue customer delight. This paper seeks to design a work‐in‐process (WIP) exception handling system (WIPEHS) not simply measuring on‐time delivery performance for managers to take necessary improvement activities. It helps managers detect abnormal WIP levels in advance, trigger rectifying actions and finally notify pertinent people to coordinate roots causes and preventive means.

The structure of WIPEHS is proposed and then constructed with a soft package, Vigilance. A typical semiconductor factory is built and production data are simulated to evaluate the effectiveness of WIPEHS.

Collecting and analyzing results from the simulated typical semiconductor factory, the paper finds that the proposed system can effectively improve on‐time delivery performance; and that durations from a WIP exception detected a WIP exception back to normal and durations between two successive WIP exceptions significantly.

It helps factories outperform due dates, achieving significantly higher performance than prior performance without the production exception handling system, which should greatly please customers.

The proposed WIPEHS provide a total solution for undesirable production variations potentially harmful to due‐date performance. It anticipates WIP exception, notifies pertinent recipients, tracks the progress of exception resolution, and provides a forum for discussion of the root causes.

The food and beverage industry, particularly the agro‐processing and packaging industry, plays a critical role in the economies of Latin America and Caribbean countries. To remain competitive and to increase competitiveness, companies operating in this industry must achieve operational efficiency – where one contributing factor would be the efficient management of their work‐in‐progress (WIP) inventories.

Constructs from related manufacturing management research areas such as manufacturing strategy and coordination theory, are incorporated into a conceptual framework to examine the reasons WIP are needed in food plants. The framework is used to inform the development of an audit tool, which is applied in a case study.

An audit tool is proposed, which can be used by practitioners to review the structural and infrastructural decisions that impact WIP.

The audit tool is applied in one case study. Further application of the tool will test its overall comprehensiveness.

The audit tool can be used as part of a structured decision making process.

The paper brings together a number of constructs to create an audit tool that can be used in both greenfield and existing plants in the food industry.

Constructing an effective production control policy is the most important issue in wafer fabrication factories. Most of researches focus on the input regulations of wafer fabrication. Although many of these policies have been proven to be effective for wafer fabrication manufacturing, in practical, there is a need to help operators decide which lots should be pulled in the right time and to develop a systematic way to alleviate the long queues at the bottleneck workstation. The purpose of this study is to construct a photolithography workstation dispatching rule (PADR). This dispatching rule considers several characteristics of wafer fabrication and influential factors. Then utilize the weights and threshold values to design a hierarchical priority rule. A simulation model is also constructed to demonstrate the effect of the PADR dispatching rule. The PADR performs better in throughput, yield rate, and mean cycle time than FIFO (First‐In‐First‐Out) and SPT (Shortest Process Time).

Compares alternative buffer control systems used in a flow process, assembly line manufacturing system. Follows a literature analysis with the use of computer simulation to assess and measure the effects of each system on overall production performance, and individual workstation utilization.

The concepts of supply chain management and quick response manufacturing systems have been forwarded in the clothing sector as a route to competitive advantage for manufacturers based in high labour cost countries. An integral part of the advantage gained via such systems is reduction in inventory throughout the supply chain. The aim of the paper is to examine the movement in inventory in the clothing sector relative to the average as obtained in the manufacturing sector as a whole and to use the results to test the hypothesis that supply chain management has progressed in the sector.

The textile industry contributes 2 and 3% to the global and Indian Gross Domestic Product (GDP), respectively. India supplies a quarter of global cotton yarn. Yet, most yarn manufacturing companies use outdated methods and lack organisational skills and strategies. Improvement in processes in India could significantly help the industry worldwide.

The variables that influence the performance of the system were identified. Their interrelationships and impact were identified from the employees in the chosen case study, a yarn manufacturing industry. A System Dynamics (SD) approach was employed to study the benefits of implementing 5S lean strategies. The impact of each variable on various performance measures such as throughput, Work In Progress, processing time, waiting time, idle time, over-processing and scraps was analysed.

Improvement in outcomes reflected an enhanced adoption of leanness in the industry. The decision-makers can utilise this study to optimise the necessary parameters in the system and attain the desired productivity levels. Better resource management and reduced processing time helped increase the despatch rate by 9.735% and decrease the WIP by 23.01%. Time management helped to reduce the inventory, idle time and waiting time. Over-processing, defects and scraps were minimised, indicating a shift towards lean.

This study pioneers the use of SD simulation models for optimising yarn manufacturing using lean strategies. Improvement in performance measures by integrating these strategies opens avenues for future research using multiple approaches to address a problem.

Implementing 5S lean principles and simulations enhances productivity, reduces waste and optimises resource management for the yarn manufacturing industry. Decision-makers can employ simulation to witness the outcomes of their changes without investing cost and time and without associated implementation risks.

The use of a simulation model to witness the benefits of incorporating lean strategies in yarn production has not been explored. This approach could help the managers and policymakers understand their existing system's shortcomings and critical areas that require improvement.

Materials management de facto has existed for many years in terms of procedures for buying and processing material to meet orders for finished products. However, the term itself first came into vogue in the mid 1960s and various commentators have pointed to different factors which have led to its evolution and growth over the past 15 or more years. Whilst any analysis of the relative importance of the various factors involved is beyond the scope of this survey, it is fair to say that a combination of pressures in the 1960s and 1970s led to a change in direction of business thinking and a search for profit contributions through the adoption of an integrated materials management approach in previously neglected areas. There is no single view about what materials management really is and the materials management concept has been given many interpretations. Academics and organisations alike interpret materials management in the light of their own experiences and perceptions.

Workload contribution calculation approaches in the existing literature overestimate or underestimate indirect workload, which increases both workload fluctuation and shop floor throughput performance. This study optimizes a Corrected Aggregate Workload (CAW) approach to control the workload contribution of workstations and Work In Progress (WIP) levels, thereby improving the shop floor throughput performance.

This study adopts simulation experiment by SimPy, and experimental factors are: (1) two workload contribution methods (CAW method and considering Position Corrected Aggregate Workload [PCAW] method); (2) two release methods (LUMS COR release and immediate release); (3) eleven workload norms for LUMS COR release (from 7- to 15-time units), and infinite workload norm for immediate release; and (4) two dispatching rules (First Come First Served, FCFS and Operation Due Date, ODD). Each scenario is replicated 100 times, and for each replication data are collected for 10,000 time units, being the warm-up period set to 3,000-time units.

The results of this study confirm that the PCAW calculation method outperforms the CAW method, especially during higher workload norm levels. The PCAW method is considered the better solution in practice due to its excellent performance in terms of percentage tardiness and mean tardiness time. The efficient workload contribution approach, as discussed in this study, has the potential to offset delivery performance loss that results from throughput performance loss.

This study proposes a novel approach that considers the workstations’ position in the routing of the job and the position of jobs CAW method. The results demonstrated that it allows shop floor throughput time to be short and feasible. It controls WIP by workload contribution of workstations, resulting in a lean shop floor. Therefore, workload contribution calculation is of particular significance for high-variety Make-To-Order (MTO) companies.

This work presents the results of a case study aimed at revitalizing an agricultural equipment manufacturing consortium facing prolonged losses. The purpose of this paper is to enhance productivity and profitability by identifying and eliminating waste within the manufacturing processes. The study uses lean principles and tools to achieve this objective.

The study begins with the creation of a questionnaire, administered to the consortium to gather insights. The questionnaire responses serve as a foundation for pinpointing critical areas in need of immediate attention. To tackle the challenge of demand forecasting without customer data, a demand forecasting model is introduced. Value stream mapping (VSM) is used to identify and highlight process inefficiencies and waste. The findings are further analyzed using a Pareto chart to prioritize waste reduction efforts. Based on these insights, the study proposes alternative manufacturing methods and waste elimination strategies. A multiphase lean framework is developed as a step-by-step roadmap for implementing lean manufacturing.

The study identifies a broken process flow within the consortium’s manufacturing processes and highlights areas of waste through VSM. The Pareto chart analysis reveals the most significant waste areas requiring immediate intervention. Recommendations for process improvements and waste reduction strategies are provided to the consortium.

This study contributes to the field by applying lean principles and tools to address the unique challenges faced by an agricultural equipment manufacturing consortium. The integration of a demand forecasting model and the development of a multiphase lean framework offer innovative approaches to enhancing productivity and profitability in this context.