Fuzzy multi-attribute decision-making for evaluating manufacturing flexibility

Evaluation of manufacturing flexibility in operations management is important to determine the competitiveness of manufacturing system, and is being increasing discussed in the literature on manufacturing system. The objective of this research is to develop a multi-attribute decision-making model based on fuzzy set theory to improving the manufacturing flexibility evaluation process. Since most information available in this stage is not numerical, fuzzy linguistic assessment is used to represent the performance rating of all flexibility metrics under flexibility dimensions and importance grade of all flexibility dimensions. This paper proposes a modified LOWA operator, which uses the maximum entropy weights, and uses it to direct computation on linguistic terms. The developed model evaluates the degree of manufacturing flexibility that can assist decision-makers, when making capital investment decisions and measuring performance, in finding the need for improving manufacturing flexibility, and in determining the dimensions of flexibility as the best directions to improvement. Examples using a case study of leading Taiwan firm in the bicycle industry are used to illustrate the concept developed. In addition, sensitivity analysis can be performed to examine the solution reasonability.     

AN OPERATIONAL PLANNING CONCEPT FOR DEEP LANE STORAGE SYSTEMS

The main advantage of deep lane storage systems compared with conventional high bay warehouses is seen in a better space utilization, because products are stored in channels one pallet behind the other. However, for deep lane storage systems the last-in-first-out principle holds and direct access to pallets is lost apart from the last pallet entering a channel. To operate deep lane storage systems effectively, namely, providing high throughput rates even at times of high storage rack utilization requires a sophisticated operational planning system. We will describe a totally new concept consisting of five modules for storage and retrieval assignments, as well as for a reorganization of storage location occupations.     

Coordinating External Manufacturing of Product Modules*

Product modularization has changed gradually from mainly being a way to bring strategic flexibility into product design, to becoming a means to reach new suppliers in a globalized world. Use of external suppliers is facilitated by the “embedded coordination” brought by standardized module interfaces which reduce the interdependence between modules manufactured by different suppliers. However, the distance between design and manufacturing is increased by heavy reliance on suppliers, and requires coordination between design and manufacturing. Hence, this article aims to identify appropriate mechanisms to enable coordination of external manufacturing of product modules. The investigation is based on two case studies in one manufacturing company that has for long relied heavily on external suppliers. The case studies identify different means, coordination mechanisms, of handling the increased distance between design and manufacturing. In addition to organizational solutions, various intermediaries including especially the supply chain function act as bridges between design and manufacturing. The appropriate mechanism to use is decided by the character of the product and the degree of upgrading. We recommend openness to adaptation to situation dynamics rather than investment in optimizing the level of integration with a particular supplier.     

A Quality Risk Management Model Approach for Cell Therapy Manufacturing

International regulatory authorities view risk management as an essential production need for the development of innovative, somatic cell‐based therapies in regenerative medicine. The available risk management guidelines, however, provide little guidance on specific risk analysis approaches and procedures applicable in clinical cell therapy manufacturing. This raises a number of problems. Cell manufacturing is a poorly automated process, prone to operator‐introduced variations, and affected by heterogeneity of the processed organs/tissues and lot‐dependent variability of reagent (e.g., collagenase) efficiency. In this study, the principal challenges faced in a cell‐based product manufacturing context (i.e., high dependence on human intervention and absence of reference standards for acceptable risk levels) are identified and addressed, and a risk management model approach applicable to manufacturing of cells for clinical use is described for the first time. The use of the heuristic and pseudo‐quantitative failure mode and effect analysis/failure mode and critical effect analysis risk analysis technique associated with direct estimation of severity, occurrence, and detection is, in this specific context, as effective as, but more efficient than, the analytic hierarchy process. Moreover, a severity/occurrence matrix and Pareto analysis can be successfully adopted to identify priority failure modes on which to act to mitigate risks. The application of this approach to clinical cell therapy manufacturing in regenerative medicine is also discussed.     

Organizational modifications to support JIT implementation in manufacturing and service operations

This study investigates JIT implementation practices and performance in manufacturing and service organizations in the US. Literature related to JIT usage and performance in both sectors is reviewed. A field study is then conducted to investigate the actual implementation experiences of a selected group of service and manufacturing users of JIT. Our findings from the literature and the field study are used to develop four research hypotheses that are tested using survey data from 130 manufacturing and 61 service firms. Manufacturing and service firms that had engaged in modifications such as operator and management training and improving linkages with suppliers prior to implementing their JIT systems experienced less implementation problems and achieved higher levels of success than firms that placed less emphasis on these modifications. This paper details and discusses these and other results from our study. In addition, managerial implications of our findings are presented.     

An Empirical Model for Managing Quality in the Electronics Industry

Much of the empirical research in the past two decades has suggested that quality management (QM) is context dependent. This research develops an empirical QM model in a technology‐based sector—electronics manufacturing. Based on quantitative and qualitative investigations of 225 electronics firms in Hong Kong and the Pearl River Delta (PRD) region of China, a path analytic model is developed. The empirical model shows that a typical quality management system (QMS) in the electronics industry is composed of four major modules, namely leadership, cultural elements, operational support systems, and process management. These modules create a series of chain effects on organizational performance, rather than acting as parallel elements with an equal impact. By quantifying their effects on organizational performance and comparing the model to others in the literature, we identify those QM constructs that are context dependent. In electronics manufacturing, process management and customer focus are more important than other elements (e.g., cultural factors) for garnering business results. This study contributes to contingency theory and research by identifying the key constructs and their relationships in a competitive, volatile, and technology‐based industry with complex supply networks.     

Decentralized WIP-oriented manufacturing control (DEWIP)

DEWIP is a manufacturing control system for job shop environments aiming at achieving short and reliable lead times by establishing WIP control loops between the manufacturing work centres. The paper describes the mode of function, the setting of parameters and simulation results of the new manufacturing control system. The setting of parameters is done with the aid of the funnel model and the theory of logistic operating curves, both developed at the Institute of Production Systems at the University of Hanover. The simulation is conducted using industrial data and makes it possible to assess DEWIP with regard to lead times, WIP level, performance and schedule reliability. DEWIP is compared both with an uncontrolled process and with the manufacturing control systems Load oriented order release (LOOR), Conwip and Polca. The results suggest that DEWIP and the models employed for the setting of parameters are suitable for job shop production and therefore offer a valuable alternative to prevailing centralized manufacturing control systems.     

An Empirical Investigation of Costs in Batching Decisions*

This paper examines the use of costs and cost functions to model lot‐sizing decisions in batch manufacturing. The cost functions used to model a wide variety of manufacturing systems are typically derived from average cost models of unconstrained inventory problems. The use of setups and average inventories as the basis for modeling the economics of a typical batch manufacturing cell is shown to be inadequate. An alternative physical model that focuses on lead times provides a model that more closely represents the underlying value of such a cell.     

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.     

Integration of the information systems in the production process: a case study

This paper evaluates the execution of an ERP – enterprise resource planning in a production process. The changes that were made to processes to make them compatible with ERP modules and adaptations that were required by the ERP implementation are presented. The presented study is different from the normal patterns of a vertical implementation, since its application is not direct. In order to use the standard modules of the ERP system, the internal processes were embellished and the data collection steps were integrated into the production process (production orders, inventory, production, daily consumption, daily output). The case study shows that the ERP implementation caused an improvement of the processes in the areas adjacent to production (purchasing, logistics, distribution, supply and sales). In conclusion, this paper presents the main advantages and disadvantages of the ERP system implementation, as well as some considerations and recommendations for the future ERP implementations.     

Search based job scheduling and sequencing with setup times

The problem of sequencing jobs on a machine in a job shop has been approached by a number of researchers and practitioners. One of the most popular methods is to apply a priority rule to the queue at each machine. The authors have previously published details of an approach which sets the priority of a job as a linear combination of the operation times and due date for that job. The coefficients in the linear combination are set by a simulation and search procedure so as to give good performance based on the performance measure specified. This paper extends this approach to include setup time factors. This extended approach is then applied to data from an actual manufacturing system. The extended approach is shown to improve the performance of the manufacturing system in relation to existing techniques.     

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.     

Simulation optimization through direct search for multi-objective manufacturing systems

Simulation modelling has been one of the most widely used techniques for analysing complex manufacturing systems. In this paper, we propose a direct search algorithm expanded from the Hooke-Jecves pattern search to systematically and efficiently locate satisfactory solutions for multi-objective simulation models. The user-specified goals can be precise and/or fuzzy. Heuristic rules stemming from the simulation result of resource statistics are incorporated into the Hooke-Jeeves pattern search. The proposed heuristic rules make the search procedure effective regardless of different initial points and various bounded ranges of decision variables. Experimental results show that the proposed approach is suitable for analysing complex manufacturing systems, in which multiple objectives and multiple decision variables are encountered.     

Scheduling two-stage production lines with multiple machines

Most manufacturing process maintain separate fabrication and assembly centres. Based on this observation, the author coincides a manufacturing process that contains two stages of production with multiple machines. The manufacturer produces a variety of products to satisfy customer demands, operates under a 'push' mode and in a ‘ make-to-order’ environment. Each customer order consists of known quantities of different products which must be delivered as a whole shipment. Periodically, the manufacturer schedules all the accumulated unscheduled customer orders. The scheduling objective is to minimize the sum of weighted customer order lead times. Such manufacturing systems are formulated as a mathematical programming problem. It is then shown that this problem is unary NP-hard and remains unary NP-hard even when all the weights are equal. Some insights about the structure of the optimal schedule(s) are provided and some special cases solved in polynomial time. Several polynomial time heuristics are proposed, and worst-case analysis of some of the heuristics are provided. Tight lower bounds are developed in order to measure the performance of the proposed heuristics. Numerical examples are presented and possible extensions are discussed.     

A simulation-based dynamic operator assignment strategy considering machine interference - a case study on integrated circuit chip moulding operations

A simulation-based dynamic operator assignment strategy is proposed considering machine interference in solving an integrated circuit moulding operation problem. The strategy iteratively solves a floating manpower operator-assignment problem between simulation-based diagnostic study and operator assignment decision. Given current-state information, it provides a means for system performance evaluation. It searches a satisfactory solution for both cycle time and service level performances by using floating manpower method. A structured experimental design is used to illustrate the effectiveness of the proposed methodology. Empirical results show promise for the proposed methodology in solving a practical application. Finally, the system implementation constraints from both hardware and management problems are addressed.     

Product universality and design for supply chain management

We describe our experience of developing models in which the principles of design for supply chain management (DFCM) have been implemented for new product development at Hewlett-Packard Company (HP). This experience arises from the development of a new product that is scheduled to be released in 1995. A key design decision faced by the product development team was whether to use a universal module or regionally dedicated modules to satisfy global market requirements. We describe a wide range of factors—including manufacturing and logistics costs—that could be used to support the design decision; these factors associated with product and process design contribute to tolal supply chain costs. We review the analytical model used to evaluate the cost and service implications of the two design alternatives. Finally, we discuss qualitative considerations that might influence the eventual decisions as well as the lessons learned from this real world experience.     

Production control for just-in-time tool-and-die manufacturing

The strategy to implement production control varies in different types of manufacturing systems. We address the issue of production control in unit-based manufacturing systems where the production batch size of the final product is one or two, the product is custom designed and is made up of numerous individual components with similar process routeings lor special machine tools, turbines, boilers, tool-and-die, injection moulding equipment, custom fabrication, etc. We have developed algorithms to generate master production schedules in this particular domain of manufacturing systems using the concept of workgroups. We show how a Kanban-based JIT shopfloor control and purchasing system can be implemented in such systems in tandem with an inventory management system by utilizing the concept of demand lists. We also propose a model for practical implementation of production control in this domain. The methodology is illustrated at a tool-and-die plant where a CIM software is used to apply the JIT-based production control. Preliminary results show a significant reduction in lead times. We try to show the relationship between research and industrial applications of productions of production control and how to bridge the gap between them.     

A Capacitated Multi‐echelon Inventory Placement Model under Lead Time Constraints

We develop an inventory placement model in the context of general multi‐echelon supply chains where the delivery lead time promised to the customer must be respected. The delivery lead time is calculated based on the available stocks of the different input and output products in the different facilities and takes into account the purchasing lead times, the manufacturing lead times, and the transportation lead times. We assume finite manufacturing capacities and consider the interactions of manufacturing orders between time periods. Each facility manages the stocks of its input and output products. The size of customer orders and their arrival dates and due dates are assumed to be known as in many B2B situations. We perform extensive computational experiments to derive managerial insights. We also derive analytical insights regarding the manufacturing capacities to be installed and the impacts of the frequency of orders on the system cost.     

Some structural properties for the just-in-time level schedule problem

Just-in-time (JIT) is a pull concept applied mainly in repetitive manufacturing systems, and it is characterized by a scenario where only the required units are produced in the required quantities at the required times. It particularly aims at eliminating wastes associated with inventories in the system. A level schedule is desirable for a JIT assembly system, as it serves as an approximation for all forms of smoothing. The min-sum formulation of the assembly line level schedule problem is one of those that has been mainly used in the literature. Using this formulation as a base, we develop some useful structural properties for the problem. Among other things, it is shown that a level schedule would tend to be more difficult to achieve for products (models) with comparatively fewer units in the products composition structure.     

基于改进策略的混合型制造/再制造系统分析

在制造和再制造并存的混合型系统中,制造商需要同时协调新产品生产过程和旧产品再制造过程,这种双向物流的集成运作使得传统的生产规划和库存管理方式不再适用,如何构建一种有效的控制策略来协调生产过程和再制造过程就显得十分关键。本文在优化库存信息的基础上提出了一种适用于混合系统的改进策略,同时考虑到系统复杂性,主要采用控制理论中的传递函数技术构建了系统模型。仿真结果表明,本文提出的改进策略不仅可以有效协调新产品生产过程和旧产品再制造过程,而且还可以显著改善系统性能。