Capacity planning with capability for multiple semiconductor manufacturing fabs

A capacity planning system (CPS) that considers the capacity and capability of equipment is developed for multiple semiconductor manufacturing fabs. On the basis of pull philosophy and the assumption of infinite equipment capacity, the system determines each lot's release time, start fab, and the capability of the equipment. CPS includes three main modules—the WIP-Pulling Module (WPM), the Workload Accumulation Module (WAM) and the Wafer Release Module (WRM). WPM pulls WIP from the end of the process route to meet the master production schedule (MPS). WAM then calculates the expected equipment loading in different time buckets. If WIP cannot meet the MPS requirement, then for each lot to be released, WRM evaluates the expected loading of many fabs, based on the lot's planned start time, and then determines the lot release time, the start fab and the equipment capability, to optimize the workload balance among all fabs. Simulation results indicate the effectiveness and efficiency of this system. A CPS that combines Adjusted Release Time (ART) and Path Load performs best in terms of three performance measures. This finding shows that CPS based on the combination of ART and Path Load can efficiently balance the equipment workload among the various fabs, on various days, and across various equipment at various levels of demands.     

Some effects of flexibility and dependability on cellular manufacturing system performance

The advantages of cellular manufacturing organization can be strongly affected by uncertainty. In particular, the effects of resource dependability on system performance are investigated. The use of routing flexibility in cellular manufacturing systems (CMS) is analyzed to search system configurations that optimize system performance. Adopting the concept of “limited flexibility” proposed in the literature, a simulation model is proposed to point out some trade-off between routing flexibility costs and benefits in a CMS with both constant and variable part family demand. Three specific problems are addressed and quantitative results, in terms of costs and lost sale performance, are provided by case examples.     

面向柔性制造车间的多目标RFID网络规划方法

针对具有多种覆盖需求的柔性制造车间RFID网络规划问题,以部署成本、阅读器干扰与阅读器效能为多优化目标,提出一种分层聚类、冗余消减与梯度下降方法集成的RFID网络规划方法,采用分层聚类算法确定RFID初始数量与部署位置,采用冗余阅读器消减算法优化RFID数量,采用梯度下降算法优化RFID部署位置从而实现网络规划多目标优化。实验研究表明,提出的方法在多目标综合性能方面优于传统基于分层聚类方法、遗传算法、粒子群与冗余消减混合方法的RFID网络规划方法,验证了该方法的有效性。     

The effect of system configuration and ramp-up time on manufacturing system acquisition under uncertain demand

The objective of this paper is to investigate the optimal allocation of capacity investments at the tactical decision-making level by incorporating the configuration characteristics of selected system alternatives comprising Dedicated Manufacturing Systems (DMS) and Reconfigurable Manufacturing Systems (RMS). Particularly, sequencing of stages in a series or a parallel configuration impacts the responsiveness in addressing capacity change requirements. We analyze what type of configuration is more suitable for a manufacturer in terms of service level and cost. We propose a mixed integer programming model by incorporating various ramp-up time patterns, which define system scalability lead time. By solving the MIP model to optimality, we aim to see how capacity is allocated to RMS and DMS based on system cost, system responsiveness, and reconfiguration speed. A discrete event simulation model is used to validate the MIP results under uncertain demand scenarios.     

Capacity planning in job-shop environment

Presented here is a computerized capacity planning system for the IBM Microcomputer family. The system maintains the profile of the job shop in a data base along with data pertinent to various products that can be manufactured in the shop. Projected orders for the planning period are input to the system with their associated quantities and delivery dates. The system uses the forward and backward loading rules in generating capacity loading scenarios. User selects the best course of action which may satisfy delivery dates subject to the limitations of the work centers. Efficiency figures are provided to aid the user in his/her decision.     

A distributed task planning system for computer-integrated manufacturing systems

A formal mathematical framework for a distributed task planning method suitable for computerintegrated manufacturing systems is proposed. All pertinent algorithms are derived. A detailed timing analysis associated with primitive actions and activities (complex tasks) execution is presented. A formal language is designed for event tracking and error specification. Based on the derived language, an error recovery mechanism (automaton) is proposed. A case study demonstrates the applicability of the presented method with and without error occurrences.Dr Kokinaki is currently Science and Engineering Research Centre, De Montfort University, UK.     

Integration of real-time planning and control in an unstructured manufacturing workcell

In this paper, we consider the problem of real-time planning and control of a robot manipulator in an unstructured workspace. The task we consider is to control the manipulator, such that the end-effector follows a path on an unknown surface, with the aid of a single camera assumed to be uncalibrated with respect to the robot coordinates. To accomplish a task of this kind, we propose a new control strategy based on multisensor fusion. We assume that three different sensors, i.e. encoders mounted at each joint of the robot with 6 d.o.f., a force-torque sensor mounted at the wrist of the manipulator and a visual sensor with a single camera fixed to the ceiling of the workcell, are available. Also, we assume that the contact point between the tool grasped by the end-effector and the surface is frictionless. To describe the proposed algorithm that we have implemented, first of all we decouple the vector space of control variables into two subspaces, and use one of the subspaces for controlling the magnitude of the contact force on the surface and the other subspace for controlling the constrained motion on the surface. In this way the control synthesis problem is decoupled and we are able to develop a new scheme that utilizes sensor fusion to handle uncalibrated parameters in the workcell and wherein the surface on which the task is to be performed is assumed to be visible, but has an apriori unknown position.     

Valuation of expansion flexibility in flexible manufacturing system investments using sequential exchange options

In this paper, a valuation approach that modifies traditional discounted cash flow (DCF) methodology is presented to incorporate the option premium of expansion flexibility while evaluating a flexible manufacturing system investment. Expansion flexibility allows for changing the production capacity in response to deviations in demand, while disregarding the assumption that management makes an irrevocable decision based on its future market expectations. Expansion flexibility provides a key strategic advantage by avoiding the large financial commitment at the initial investment stage and enabling investment in a phased manner according to the changes in market conditions. The aim of this paper is to present a thorough valuation methodology that accounts for both the benefits of keeping the option to expand alive and the loss of market share to competing firms if the expansion investment were delayed. In this paper, the value of expansion flexibility is computed using sequential exchange options. The proposed method employs an analytic approximation scheme for valuing American exchange options on dividend-paying assets. A numerical example demonstrates the application of the valuation framework. The options approach that incorporates the expansion flexibility option into the analysis results in a higher value than the standard DCF approach, which ignores the value of the option to expand. We also perform sensitivity analyses to see whether the expansion option increases in value in cases of high uncertainty where management can respond flexibly to new market information, and where the investment analysis ignoring flexibility yields a marginally positive net present value. The results of the proposed valuation framework are presented in comparison with a previous model that ignores the opportunity cost of delaying expansion investment.     

A practical approach to a process planning expert system for manufacturing processes

In this paper the methodical techniques applied by the human process planning expertise is simulated. It considers the process plans design, or process selection. Software modules are designed to generate a process plan or several plans for a new part according to the input data from its engineering drawing. A specific module for each surface type, to match the surface parametric data and the required quantities with respect to the capability matrices, in order to locate the most eligible process plan is identified and used.     

Capacity planning for packaging industry

This paper presents a capacity planning system (CPS) to generate a feasible production schedule, improve production efficiency, and avoid overcapacity for the packaging industry. CPS applies the concept of workload leveling and finite capacity planning to assign orders to production lines by considering several production characteristics such as drying time, quantity splitting owing to the cutting pattern of the product type, and the variability of machine capacity threshold. CPS consists of five modules, namely, order treatment module (OTM), order priority module (OPM), lot release module (LRM), workload accumulation module (WAM), and workload balance module (WBM). The experimental design is used to evaluate the effectiveness and efficiency of the proposed CPS with five factors (number of orders, order size, order size variance, order priority, and balance policy) with various levels and three response variables, namely, machine workload balance, order due date deviation, and lateness. Moreover, this result extends into finding the best settings of order priority and balance policy to generate the best favorable responses under the given three environment factors.     

Hierarchical production planning for complex manufacturing systems

A hierarchical approach to production planning for complex manufacturing systems is presented. A single facility comprising a number of work-centers that produce multiple part types is considered. The planning horizon includes a sequence of time periods, and the demand for all part types is assumed known. The production planning problem consists of minimizing the holding costs for all part types, as well as the work-in-process and the backlogging costs for the end items. We present a two-level hierarchy that is based on aggregating parts to part families, work-centers to manufacturing cells and time periods to aggregate time periods. The solution at the aggregate level is imposed as a constraint to the detailed level problems which are formulated for each manufacturing cell separately. This architecture uses a rolling horizon strategy to perform the production management function. We have employed perturbation analysis techniques to adjust certain parameters of the optimization problems at the detailed level to reach a near-optimal detailed production plan. Numerical results for several realistic example problems are presented and the solutions obtained from the hierarchical and monolithic approaches are compared. The results indicate that the hierarchical approach offers major advantages in computational efficiency, while the loss of optimality is acceptable.     

A hierarchic approach to production planning and scheduling of a flexible manufacturing system

The paper deals with the problem of improving the machine utilization of a flexible manufacturing cell. Limited tool magazine space of the machines turns out to be a relevant bottleneck. A hierarchic approach for this problem is proposed. At the upper level, sets of parts that can be concurrently processed (batches) are determined. At the lower levels, batches are sequenced, linked, and scheduled. Methods taken from the literature are used for the solution of the latter subproblems, and an original mixed integer programming model is formulated to determine batches. The proposed methods are discussed on the basis of computational experience carried out on real instances.     

The activity-based aggregate production planning with capacity expansion in manufacturing systems

This paper builds a mixed integer linear programming (MILP) model to mathematically characterize the problem of aggregate production planning (APP) with capacity expansion in a manufacturing system including multiple activity centers. We use the heuristic based on capacity shifting with linear relaxation to solve the model. Two linear relaxations, i.e., a complete linear relaxation (CLR) on all the integer variables and a partial linear relaxation (PLR) on part of the integer variables are investigated and compared in computational experiments. The computational results show that the heuristic based on the capacity shifting with CLR is very fast but yields low-quality solution whereas the capacity shifting with PLR provides high-quality solutions but at the cost of considerable computational time. As a result, we develop a hybrid heuristic combining beam search with capacity shifting, which is capable of producing a high-quality solution within reasonable computational time. The computational experiment on large-scale problems suggests that when solving a practical activity-based APP model with capacity expansion at the industrial level, the capacity shifting with CLR is preferable, and the beam search heuristic could be subsequently utilized as an alternative if the relaxation gap is larger than the acceptable deviation.     

Integrated yet distributed operations planning approach: A next generation manufacturing planning system

Present paper envisages the need for an innovative operations planning system to handle the challenges and opportunities offered by next industrial revolution called Industry 4.0 or smart manufacturing. In specific, to embrace the increasing level of automation in manufacturing industries, the obligation of joint consideration of multiple operations functions is realized. On the other hand, quick response to dynamic conditions created by machine failures, change in demand, uncertainty in supply, etc., is important in captivating the advantages of the digitization in industries. Easing out the computational complexity, imposed by the integration of multiple functions, therefore, becomes an important aspect of next generation manufacturing planning systems. Consequently, in this paper, an agent-based approach is engineered around the opportunities offered by modern digital factory viz., intelligence at the shop-floor and ubiquity of wireless communications. While intelligence at shop-floor allows distributing the decision-making tasks to various functional agents, the communication among the agents makes it feasible to incite integrated view through the coordination agent. The approach is demonstrated for a representative industrial environment of an automotive plant. Further, comparison over conventional approaches, computational comparison, effect of degree of integration, and performance of the approach under dynamic conditions are investigated. Finally, the approach is comprehensively evaluated to analyze its robustness and implications in various manufacturing settings. This extensive investigation shows that the proposed operations planning system has capability to apprehend the benefits from next generation intelligent factory.     

Tolerance evaluation of flexible manufacturing architectures

Within the framework of FMS dependability, this article aims to apply the concept of tolerance to flexible manufacturing architectures. This enables flexible architectures to be studied and the one that could best react if failure occurs to be chosen. The methods proposed here are based on a process representation. They could be used on a designed architecture in a feedback process: The analysis is performed off line in order to check whether the workshop is tolerant or the addition of some flexibilities can make the system more tolerant.     

Product mix strategy and manufacturing flexibility

The manufacturing industry is facing a turbulent and constantly changing environment, with growing complexity and high levels of customisation. Any investment solution should address these problems for a dynamic market and within limited budget boundaries, so that companies try to remain competitive. The authors propose a real options model to support firms making important investment decisions, specifically decisions associated with the acquisition of new equipment aimed at allowing firms to increase their manufacturing flexibility for the production of both standard and customized products. This paper is partially based on a real operating experience related to visual finishing technology features in an industrial company that conforms to the definitions of the product mix. The authors’ motivation for this work is driven by firms’ desire to satisfy specific customer needs, and to respond to them quickly under uncertain demand. Our goal, using theories from finance, production management, and product offering management, is to conclude that there is a relevant difference between the evaluation of the technology that is to be chosen, and the potential value due to product mix adaptations that are able to provide the maximum return from investment. We address problems related to standard and customized production systems, and the decision to invest in a set of resources that will enable this choice.     

Design and planning problems in flexible manufacturing systems: a critical review

This review paper describes the state-of-the-art research on flexible manufacturing systems (FMS) design and planning issues. The emphasis is on presenting research results coming out of the current FMS literature that help the FMS manager in setting up a highly efficient manufacturing system. In addition to that, it discusses relevant research contributions after 1986, that were not part of any of the previous survey papers on operations research models for FMSs. Also, applications of combinatorial optimization approaches to FMS planning problems are adequately exposed in the paper.     

Production planning and worker training in dynamic manufacturing systems

Production planning is a vital activity in any manufacturing system, and naturally implies assigning the available resources to the required operations. This paper develops and analyzes a comprehensive mathematical model for dynamic manufacturing systems. The proposed model integrates production planning and worker training considering machine and worker time availability, operation sequence and multi-period planning horizon. The objective is to minimize machine maintenance and overhead, system reconfiguration, backorder and inventory holding, training and salary of worker costs. Computational results are presented to verify the proposed model.     

装备制造企业如何选择柔性制造策略——基于制造合格率视角

柔性制造是装备制造企业应对制造稳定性干扰、提升竞争优势的重要手段.注意到现有文献较少关注制造稳定性与制造柔性量化这一不足,分别用制造合格率和制造冗余量刻画制造稳定性和制造柔性,并在此基础上构建一个关于装备制造企业制造合格率、制造柔性以及制造利润的统一分析框架,用以考察并揭示装备制造企业柔性制造策略对其应对制造稳定性的影响.研究结果表明:柔性制造策略的开展,有助于装备制造企业提高应对环境变化的能力,保证产品质量与数量,进而促进制造利润增长;当单位制造成本较小时,制造柔性水平与制造合格率呈倒U型变化趋势;当单位制造成本较大时,制造柔性水平与制造合格率呈正相关关系;单位质检成本的提高会迫使装备制造企业降低制造柔性水平,并影响企业应对制造稳定性的能力,最终导致制造利润受损.     

Knowledge based manufacturing system (KBMS)

Production management, in batch type manufacturing environment, is regarded by the current research community as a very complex task. This paper claims that the complexity is a result of the system approach where management performance relies on decisions made at a too early stage in the manufacturing process. Decisions are made and stored in company databases by engineers who are neither economists nor production planner’s experts. This paper presents a new method where engineer’s task is not to make decisions but rather to prepare a knowledge-based “road map”. The road map method does introduce flexibility and dynamics in the manufacturing process and thus simplifies the decision making process in production planning. Each user will generate a routine that meets his/her needs at the time of needs by using KBMS CAPP. Thereby this method increases dramatically manufacturing efficiency.