A simulation study of dispatch rules for reducing flow times in semiconductor wafer fabrication

Semiconductor wafer fabrication involves very complex process routing, and reducing flow times is very important. This study reports a search for better dispatch rules for achieving the goal of reducing flow times, while maintaining high machine utilization. We explored a new simulation-based dispatch rule and a queue prediction dispatch rule. Using simulation experiments and an industrial data set, we also compared several other dispatch rules commonly used in semiconductor manufacturing with our proposed dispatch rules. Among these rules, in addition to the simulation-based dispatching rule, the shortest-remaining-processing-time, earliest-due-date and leastslack rules also performed well in terms of reducing flow times. The reasons behind these good rules are discussed in this paper. Based on the previous works and this study, accurately predicting and effectively utilizing future flow times can improve the quality of production management decisions.     

Adaptive Spatial Sampling of Contaminated Soil

Suppose that a residential neighborhood may have been contaminated by a nearby abandoned hazardous waste site. The suspected contamination consists of elevated soil concentrations of chemicals that are also found in the absence of site-related contamination. How should a risk manager decide which residential properties to sample and which ones to clean? This paper introduces an adaptive spatial sampling approach which uses initial observations to guide subsequent search. Unlike some recent model-based spatial data analysis methods, it does not require any specific statistical model for the spatial distribution of hazards, but instead constructs an increasingly accurate nonparametric approximation to it as sampling proceeds. Possible cost-effective sampling and cleanup decision rules are described by decision parameters such as the number of randomly selected locations used to initialize the process, the number of highest-concentration locations searched around, the number of samples taken at each location, a stopping rule, and a remediation action threshold. These decision parameters are optimized by simulating the performance of each decision rule. The simulation is performed using the data collected so far to impute multiple probable values of unknown soil concentration distributions during each simulation run. This optimized adaptive spatial sampling technique has been applied to real data using error probabilities for wrongly cleaning or wrongly failing to clean each location (compared to the action that would be taken if perfect information were available) as evaluation criteria. It provides a practical approach for quantifying trade-offs between these different types of errors and expected cost. It also identifies strategies that are undominated with respect to all of these criteria.

     

Work force scheduling with the search decision rule

This paper presents the results of a simulation study of the application of the search decision rule to work force scheduling for a manufacturing firm. The problem is of a mixed structure which includes fixed charge components (hiring and training costs), integer variables (work force size in each period), and interacting variables (work force changes, hiring and training costs, and overtime costs). With these elements present, the search decision rule produced lower total costs than the actual company decisions had over the simulated time period. The technique was found to be (1) flexible, (2) easily understood and implemented, and (3) computationally efficient, requiring only a few seconds of computer time per run.     

Capacity management through Lagrangean relaxation: an application to tyres production

A new integrated approach to capacity management in complex manufacturing systems is developed and the resulting framework is applied to a case study in tyre production. A hierarchical multilayered decomposition of the planning process is proposed, in which lower layers provide an increased level of detail and accuracy in capacity representation and analysis. Thus, a large and comprehensive model describing the manufacturing system is subdivided into smaller sub-models via relaxation and decomposition techniques. The Lagrangean multipliers provide a bi-directional link among different layers, reducing the risk of sub-optimization and infeasibility of the aggregate plans. Each of the sub-models is easier to solve than the original one and involves a different set of decision variables. Moreover, they relate to different levels of the management hierarchy, so that there emerges a strict correspondence between the decomposition scheme and the decision process underlying capacity management.     

物流敏捷调运决策支持系统的研究

由于物流敏捷调运优化方案的生成过程,本质上是一个决策过程。针对各决策环节,提出了借鉴IDEF0方法描述的敏捷调运优化适度递阶控制模型,在此基础上构建了决策支持系统总体框架。针对该决策支持系统运行模块,提出了基于敏捷性准则的运行控制思想。进而,对该决策支持系统中的数据库系统、模型库与方法库进行了研究,利用递阶设计思想设计了数据库的三大体系,提出了以"剩余装载总量"极小化为目标的物流敏捷调运优化(0-1)_h模型和对分搜索算法。通过对搜索次数的估计来衡量(0-1)_h模型求解算法的计算复杂性,结果表明该算法效率较高。     

Design of Stockless Production Systems

In make‐to‐stock production systems finished goods are produced in anticipation of demand. By contrast, in stockless production systems finished goods are not produced until demand is observed. In this study we investigate the problem of designing a multi‐item manufacturing system, where there is both demand‐ and production‐related uncertainty, so that stockless operation will be optimal for all items. For the problem of interest, we focus on gaining an understanding of the effect of two design variables: (i) manufacturing speed—measured by the average manufacturing rate or, equivalently, the average unit manufacturing time, and (ii) manufacturing consistency—measured by the variation in unit manufacturing times. We establish conditions on these two variables that decision makers can use to design stockless production systems. Managerial implications of the conditions are also discussed.     

Fix-and-optimize and variable neighborhood search approaches for multi-level capacitated lot sizing problems

In this paper, a new fix-and-optimize (FO) approach is proposed for two dynamic multi-level capacitated lot sizing problems (MLCLSP), the MLCLSP without setup carryover and the MLCLSP with setup carryover. Given an MIP model of a lot sizing problem, the approach iteratively solves a series of sub-problems of the model until no better solution can be found. Each sub-problem re-optimizes a subset of binary decision variables determined based on the interrelatedness of binary variables in the constraints of the model, while fixing the values of the other binary variables. Based on the FO, a variable neighbourhood search (VNS) approach for the MLCLSP without setup carryover is also developed, which can further improve the solution obtained by the FO by diversifying the search space. Numerical experiments on benchmark instances show that both our FO and VNS approaches can obtain a better solution for most instances compared with that found by the fix-and-optimize approach proposed by Helber and Sahling (International Journal of Production Economics 2010;123:247–256).     

多标准决策表中发现概率规则的变精度粗糙集方法

用优势关系代替不可分辨关系,本文提出了一种可以从多标准决策表中获取概率规则的扩展变精度粗糙集模型,该模型能够处理多标准决策表中可能的不一相容性,获取由偏好对象组成的概率决策规则集,并导出事例决策系统的偏好模型。研究结果表明:基于优势关系,从多标准决策表中获取的最小概率规则集,使用的条件数量较少,且导出规则的数量较少、较强。     

Optimal timing of investments in advanced manufacturing systems under competition

Large initial investment in advanced manufacturing systems (AMS) makes it imperative to develop economic justification methods. Once the new system has been properly justified, a critical issue facing the firm is the optimal timing of the installation in an industry. In this paper we use a game-theoretic model by which the optimal timing of the investments in AMSs is analysed. The existence of timing equilibria is demonstrated and simple decision rules of optimal strategy are provided. Economic interpretations of the decision rules are subsequently made clear. Finally, illustrative examples are used to demonstrate the correctness and usefulness of the analysis.     

Shop floor characteristics influencing the use of advanced planning and scheduling systems

The purpose of this article is to investigate how the manufacturing process, the shop type and the data quality, i.e. the shop floor characteristics, influence the use of advanced planning and scheduling (APS) systems in production activity and control (PAC). The methodology implemented is a multiple case study at three case companies. Each company has different shop floor characteristics, but all use a scheduling module in an APS system, which supports production scheduling. A theoretical framework is developed suggesting how APS system are used in the PAC activities, and which major aspect to consider. The case analysis shows that the scheduling module in APS system, foremost supports sequencing and dispatching. In particular, the shop type is influenced by the decision of how often the APS runs and what freedom is given to the shop floor. The manufacturing process influences how the dispatch list is created. Contrary to the literature presuming that APS systems are most suitable in job shop processes, it is found that the manufacturing process is not a crucial factor when deciding whether APS systems are an appropriate investment. It is found that the level of data quality needed in the APS system depends to a large extent on how the dispatch list is used. For example, is the dispatch list used as a guideline, not a regulation, the need for accurate data in the module is reduced. This article extends the previous literature concerning APS systems by analysing how APS systems influence PAC as a whole and increase the understanding of the challenges of using APS systems in PAC.     

基于图的广度搜索的进度生成机制

启发式算法是解决资源受限的项目调度问题的经典方法之一，通常用来生成元启发算法初始解，传统的串行（SSGS）和并行（PSGS）是生成项目调度方案的经典机制，本文基于图的广度优先搜索算法，提出了一种考虑任务节点位置因素的广度生成机制（BSSGS），并验证了算法的效果。借鉴广度搜索算法定义进度生成机制中的当前任务集合C、候选任务集合D以及阶段变量g等，对各任务节点进行层次划分并定义任务调度秩序；结合优先规则选择候选任务j^*并进行资源R_k（t）调度更新，进而生成完整的调度方案；案例分析表明新机制在满足优先规则和资源约束的同时兼顾了任务节点在网络中位置因素，拥有对于局部复杂网络不回避，对关键节点及时调度等明显优势；选择PSPLIB中算例，在不同优先规则下对新机制进行了测试，测试结果表明新的进度生成机制在LPT、SPT、MTS和MIS等优先规则下，在平均最短工期、平均资源利用率及最优调度方案率等方面优于串行和并行进度生成机制，且算法时间复杂度与传统机制相比并未增加，仍为O（J²，K）。     

A MODEL FOR SWITCHING DISPATCHING RULES IN REAL TIME IN A FLEXIBLE MANUFACTURING CELL

We model choice of dispatching rules in real time (system state dependent) as a pattern recognition problem, using a modified version of Data Envelopment Analysis. A data base of system state and performance values is created from extensive simulation, and this data base is used to train the pattern-recognition model. Our results show that the model is very effective in choosing a mix of dispatching rules over a period of time, varying the mix with system objectives, and performing better than the strategy of using fixed rules. We show how “If-Then” decision rules can be created from the model and portrayed in a decision-tree-like diagram. Since such decision rules are based on rigorous mathematical foundations, optimization will be ensured in our approach.     

Designing Referral Network Structures and Decision Rules to Streamline Provision of Urgent Health and Human Services*

This study uses fully factorial computer simulation to identify referral network attributes and referral decision rules that streamline the routing of people to urgent, limited services. As an example of a scenario, the model represents vaccine delivery in a city of 100,000 people during the first 30 days of a pandemic. By modeling patterns of communication among health care providers and daily routing of overflow clients to affiliated organizations, the simulations determine cumulative effects of referral network designs and decision rules on citywide delivery of available vaccines. Referral networks generally improve delivery rates when compared with random local search by clients. Increasing the health care organizations’ tendencies to form referral partnerships from zero to about four partners per organization sharply increases vaccine delivery under most conditions, but further increases in partnering yield little or no gain in system performance. When making referrals, probabilistic selection among partner organizations that have any capacity to deliver vaccines is more effective than selection of the highest‐capacity partner, except when tendencies to form partnerships are very low. Implications for designing health and human service referral networks and helping practitioners optimize their use of the networks are discussed. Suggestions for using simulations to model comparable systems are provided.     

Information-Processing Alternatives for Coping with Manufacturing Environment Complexity

Investment in information systems and technology is often justified as a necessary strategy for coping with the increased complexity and information needs of today/s manufacturing environments. However, the world class manufacturing paradigm suggests that increased complexity is not always necessary to meet the needs of markets and customers. Galbraith/s (1973, 1977) seminal information-processing model is applied to a manufacturing environment, supported by the world class manufacturing paradigm, to test the role of various information-processing alternatives for coping with increased environmental complexity. Moderated regression and multiple discriminant analysis are used to test hypotheses in a sample of 164 manufacturing plants. Environmental complexity was found to be related to manufacturing performance for each of the five dependent variables. This relationship was moderated by at least one information-processing alternative for each dependent variable, including self-contained tasks, lateral relations, and environmental management strategies for reducing manufacturing, supplier, and goal diversity. Investments in information systems and reduction of labor and customer diversity did not moderate this relationship. Practices that were found to be particularly effective in moderating this relationship included the use of multifunctional employees, communication of manufacturing strategy, coordination of decision making, product design simplicity, reduction of parts counts, supervisory interaction facilitation, recruiting and selection for flexible employees, JIT practices, blanket purchase orders, and strong customer relationships.     

An empirical study of an inventory-distribution system

This paper discusses the simulation results of a system consisting of a factory warehouse, and five regional distribution centers, each handling the same four products. The independent variables are demands, leadtimes, cost-rate structures. The basic data for this study has been taken from an appliance manufacturing company. Simulation experiments were conducted for three levels of each of the independent variables. The performance of the systems was measured against five important management criteria: average investment in inventories, average annual inventory carrying cost, average shortage cost per year, average reordering cost per year, and total number of reorders within the system per year. Analysis of variance was used to investigate the respective influence of each of the independent variables on each individual performance measure. The results of our study are new and of special interest, because they highlight the differences between the performance trends resulting from a single-item model and those resulting from a complex system, in terms of variations of the independent variables. This study proves that the trend of any performance-measure provided by a single-item single-location model should never be used to project that very trend of the aggregate performance of a complex inventory-distribution system.     

Becoming the best: by beating or ignoring the best? Toward an expanded view of the role of managerial selection in complex and turbulent environments

This paper explores how the rules that guide search affect organizational adaptation in complex and turbulent environments. Our consideration of such rules extends beyond search scope—i.e., exploitation of current technologies vs. exploration of new technologies—to include focus on competition. We consider two types of competitive focus—i.e., external, where the choice of focal technology to be improved is influenced by information about other organizations and internal, where it is not influenced by others. We refer to this expanded set of rules as managerial selection and vary it to explore how it affects organizational adaptation. Employing an agent based simulation model, built on the framework of NKC fitness landscapes, we consider multiple types of interdependencies within and between technologies and across competitors. We show that in the presence of these multiple interdependencies, the ability of organizations to adapt is conditioned as much or more by the focus of search than by its scope. In particular, we observe that in simple and stable environments, organizational adaptation is enhanced by an external focus but in complex and turbulent environments, such external focus is counterproductive.     

Optimal Acquisition of FMS Technology Subject to Technological Progress*

In order to gain competitive advantage, a firm must link its technology choice to its total manufacturing strategy and business unit's goals. A dynamic model is presented to examine the strategic decision concerning the acquisition of flexible manufacturing systems (FMS) technology. A major contribution of this model is its ability to capture the strategic benefits of FMS with respect to economies of scope and technological progress. Decisions such as the timing and size of new technology acquisition and the scrapping of conventional capacity are explored as a firm plans for the upgrading of its facility to meet future dynamic strategic goals. This model may be used to assist with strategic planning because it identifies the critical relationships and trade-offs between various exogenous forces (such as market growth or decay, the cost of acquiring flexible manufacturing systems, and the rate of technological progress) and the decision variables considered.     

Decision support flexible manufacturing systems

The justification of flexible manufacturing systems (FMS) is a topic that has gained a lot of attention due to the strategic effect it has on the competitive stature of industrial firms. The decision to convert to FMS should follow a pattern of feasibility assessments, cost/benefit analysis where consideration of issues such as increased quality, productivity and capability as well as tangible benefits takes place. Difficulties, however, arise in the modeling of the behavior of the proposed FMS. This paper introduces the design of a decision support framework that aids the strategic planner in simulating the performance of proposed FMS and in determining the parameters that affect the costs and benefits, tangible and intangible, of such a system. The decision support system (DSS) allows the user to use subjective evaluations of benefits accruing from intangible considerations of new product design, faster turnaround on design-to-market cycles and new marketing strategies in fragmented markets. The DSS enhances the examination of issues such as changing demand, varied tasks and routings, job and machine flexibility, etc. which affect costs and benefits. It performs these important functions by allowing for the development of scenarios that aid in the evaluation of the effect of the conversion from non-flexible to flexible manufacturing on the organization's financial position.     

Simplified production management software for the small manufacturing firm

This paper proposes design rules in order to simplify current MRP II software systems and make them suitable for the small manufacturing firm. Simplification rules apply to production data management by reducing database complexity. This has consequences for medium-term requirements planning which is moved toward the realization of simultaneous material and capacity planning. The simplification procedure is completed by applying aggregate decision models to shop floor control which allow the introduction of a minimal transaction processing system. Object-oriented analysis concepts are used for the design of the primary production data model, which has a consistent effect on transaction data and decisional procedures throughout the whole production management software system.