Development of an algorithm for the application of Group Technology in the design of Manufacturing Systems

The Group Technology theory identifies and groups similar parts into families and machines into cells, advantages being in the similarity of the parts made in each cell, and designing and manufacturing. The benefits are: simple material flow, cost reduction in material handling, reduction in work in progress, reduction in the cycle time and set-up time, increased manufacturing flexibility, increased quality, and increased job satisfaction. The objective of the work presented in this paper was to develop a Group Technology (GT) algorithm by means of cell analysis for the design of the productive system to batch production, e.g. water heater manufacturing, system manufacturing, lathes manufacturing, etc. The TGIP algorithm allows the definition of technical and economical parameters for the application of Group Technology, also taking into account the demand for the performance of the algoof heating gasrithm. The benefits of the algorithm developed are the focus on solving the case of multiple machines and the assignment of the parts to the groups related to the load of the machines; also it allows the definition of technical and economical parameters to differentiate the machines that do the same operation or even the consideration of the demand for a certain period of time.     

A Virtual Cellular Manufacturing Approach to Batch Production*

In this paper, Virtual Cellular Manufacturing (VCM), an alternative approach to implementing cellular manufacturing, is investigated. VCM combines the setup efficiency typically obtained by Group Technology (GT) cellular manufacturing (CM) systems with the routing flexibility of a job shop. Unlike traditional CM systems in which the shop is physically designed as a series of cells, family-based scheduling criteria are used to form logical cells within a shop using a process layout. The result is the formation of temporary, virtual cells as opposed to the more traditional, permanent, physical cells present in GT systems. Virtual cells allow the shop to be more responsive to changes in demand and workload patterns. Production using VCM is compared to production using traditional cellular and job shop approaches. Results indicate that VCM yields significantly better flow time and due date performance over a wide range of common operating conditions, as well as being more robust to demand variability.     

制造柔性的期权特征及其经济价值度量方法

本文分析了制造柔性的内涵,对其从生产状态变化的目标和产生来源进行了分类,并对制造柔性从期权的视角重新加以了表述.然后提出当存在市场需求、产品价格和可变成本三种不确定源的情形下制造柔性的多阶段期权定价模型,最后结合蒙特卡洛法实现了对项目投资决策阶段柔性经济价值的度量.     

A methodology for the design of manufacturing systems using group technology

The primary objectives in implementing computer integrated manufacturing systems (CIMS) are to improve quality, enhance flexibility, and increase productivity. One of the approaches used to achieve these objectives is to organize and group the production machines into manufacturing cells using group technology concepts. Cellular manufacturing allows small batch production to gain economic advantages similar to mass production while maintaining the flexibility of job shop production. This paper presents a methodology which uses design and manufacturing attributes to form manufacturing cells in a computer integrated manufacturing setting. The methodology is implemented in two phases. In phase I, parts are grouped into part families based on their design and manufacturing attributes. In phase II of the methodology, the machines are grouped into manufacturing cells based on relevant operational costs, and the various cells are assigned part families using an optimization technique. The optimization technique employs integer programming to minimize the total operational costs.     

Scheduling with Sequencing Flexibility*

This study examines the effects of sequencing flexibility on the performance of rules used to schedule operations in manufacturing systems. The findings show that taking advantage of even low levels of sequencing flexibility in the set of operations required to do a job results in substantial improvement in the performance of scheduling rules with respect to mean flowtime. Differences in the mean flowtime measure for various rules also diminish significantly with increasing sequencing flexibility. Performance improvements additionally result for such due-date related performance measures as mean tardiness and the proportion of jobs tardy. At high levels of sequencing flexibility, some nonparametric scheduling rules outperform the shortest processing time rule in terms of the mean flowtime criterion. Rules based on job due dates also outperform rules based on operation milestones in terms of tardiness related criteria at high levels of sequencing flexibility. The implications of these findings for the design of manufacturing systems and product design are noted.     

考虑需求波动的单元装配系统构建问题的多目标模型

顾客个性化需求的增强导致企业需要应对动态变化的市场需求,在非确定性需求的环境下提升生产效率和应变能力。日本式单元装配模式以其较高的生产效率和柔性已经逐步成为应对多品种小批量需求的生产方式。由于现有研究多集中于确定性需求,本文针对日本式单元系统构建问题的特点,考虑需求波动的情境下流水线装配向单元装配系统转化问题,构建单元装配系统转化的多目标优化模型。该模型以最小化总加工周期的期望和方差为目标,决策单元装配系统的构建方案,以提升需求波动情境下系统的稳定性和对需求波动的应变能力。根据问题特点设计基于NSGA-Ⅱ的优化算法求解大规模问题,并结合文献数据说明了模型的应用。数值算例验证了方法的有效性,结果表明考虑需求波动情境下的单元系统构建可以提升生产系统应对波动需求的能力以及稳定性。     

Real-time operation selection in an FMS using simulation- a fuzzy approach

Production management and scheduling problems in flexible manufacturing systems (FMSs) are more complicated than those problems in job shops and transfer lines. Due to the flexibility of FMSs, alternative operation is common. When considering the operational problems of FMSs such as scheduling, simulation methodology seems to be useful to address these issues. Real-time scheduling schemes use simulation techniques     

A simulation analysis of the impact of family configuration on virtual cellular manufacturing

Past research has shown that it is possible to simultaneously achieve the setup efficiencies of traditional cellular manufacturing systems and the routeing flexibility of a job shop by viewing cells not as permanent, physical structures, but as temporary, 'virtual' entities. This research demonstrates that the advantages of virtual manufacturing cells can be obtained over a range of part family configurations. In particular, virtual cellular manufacturing is robust to changes in the number and size of families being processed. Further, the research shows that the benefits can be obtained under setup conditions impartial to a family-oriented part environment.     

Market Good Flexibility in Capacity Auctions

We consider the allocation of limited production capacity among several competing agents through auctions. Our focus is on the contribution of flexibility in market good design to effective capacity allocation. The application studied is a capacity allocation problem involving several agents, each with a job, and a facility owner. Each agent generates revenue by purchasing capacity and scheduling its job at the facility. Ascending auctions with various market good designs are compared. We introduce a new market good that provides greater flexibility than those previously considered in the literature. We allow ask prices to depend both on agents’ utility functions and on the number of bids at the previous round of the auction, in order to model and resolve resource conflicts. We develop both optimal and heuristic solution procedures for the winner determination problem. Our computational study shows that flexibility in market good design typically increases system value within auctions. A further increase is achieved if each agent is allowed to bid for multiple market goods at each round. On average, the multiple flexible market goods auction provides over 95% of the system value found by centralized planning.     

基于同质设备多台配置的独立生产单元构建决策

单元化生产作为一种较好实现生产柔性与生产效率融合的先进生产方式,在变种变量需求环境下它已被大量生产企业特别是装配式生产企业所采用。生产单元构建问题是单元化生产系统设计的关键问题和首要问题,也是单元化生产研究领域的一个热点。本文研究设备易复制情形下,通过配置多台同质设备来实现生产单元间无物料移动,并保证生产单元间工作量均衡的独立生产单元构建问题。本文在综合考虑换装时间、加工顺序、设备生产能力、产品需求量等多个实际生产要素的基础上,建立了以平均总流程时间和各生产单元总流程时间与平均总流程时间偏差最小为目标的数学模型,并开发了一个启发式算法来求解数学模型,最后通过数值算例验证了模型和算法的有效性。     

The impact of the product mix on the value of flexibility

Product-mix flexibility is one of the major types of manufacturing flexibility, referring to the ability to produce a broad range of products or variants with presumed low changeover costs. The value of such a capability is important to establish for an industrial firm in order to ensure that the flexibility provided will be at the right level and used profitably rather than in excess of market requirements and consequently costly. We use option-pricing theory to analyse the impact of various product-mix issues on the value of flexibility. The real options model we use incorporates multiple products, capacity constraints as well as set-up costs. The issues treated here include the number of products, demand variability, correlation between products, and the relative demand distribution within the product mix. Thus, we are interested in the nature of the input data to analyse its effect on the value of flexibility. We also check the impact at different capacity levels. The results suggest that the value of flexibility (i) increases with an increasing number of products, (ii) decreases with increasing volatility of product demand, (iii) decreases the more positively correlated the demand is, and (iv) reduces for marginal capacity with increasing levels of capacity. Of these, the impact of positively correlated demand seems to be a major issue. However, the joint impact of the number of products and demand correlation showed some non-intuitive results.     

Production planning of mixed-model assembly lines: a heuristic mixed integer programming based approach

Process technology capabilities are becoming increasingly important as flexible manufacturing continues to be more prevalent, and as competition compels companies to provide expanded variety, at ever lower cost, so introducing plant and processes technological constraints. Model flexibility can also benefit from an appropriate production planning process, especially concerning mixed-model assembly lines, since it can facilitate master scheduling and line balancing activities, which are essential aspects of flexibility. Robust and practical planning approaches have to take into account two different aspects: the first consists in ensuring that the elaborated aggregate plan can be disaggregated into at least one detailed feasible plan for the realised demand, whereas the second in ensuring that this detailed plan is feasible at the operational level. This article faces the model flexibility challenge, reviewing and discussing the planning problem of a real world assembly manufacturing system, producing high volume and a variety of agricultural tractors and machines, analysing and resolving some important issues related to technological, organisational and managerial constraints. This article illustrates the implementation of an Advanced Planning System integrated with a mixed integer-programming model, which is solved by a new iterative heuristic approach capable of achieving interesting planning improvements for model-flexibility management.     

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.     

MULTI‐VENDOR SOURCING IN A RETAIL SUPPLY CHAIN*

This paper describes a methodology for managing capacity, inventory, and shipments for an assortment of retail products produced by multiple vendors. The vendors differ in lead times, costs, and production flexibility. Product demand is uncertain and fluctuates over time. We develop an optimization model to choose the production commitments that maximize the retailers expected gross profit, given demand forecasts and vendors capacity and flexibility constraints. The model has been incorporated into a decision support system, developed in collaboration with supply chain planners at a global retailer of seasonal and fashion merchandise. The software has been tested by two major retailers.     

AN OVERVIEW OF TRADEOFF CURVES IN MANUFACTURING SYSTEMS DESIGN

In this paper we review the use of tradeoff curves in the design of manufacturing systems that can be modeled as open queueing networks. We focus particularly on the tradeoff between expected work-in-process (or product leadtime) and capacity investment in job shops. We review the algorithms in the literature to derive tradeoff curves and illustrate their application in evaluating the efficiency of the system, in deciding how much capacity to have, how to allocate resources between the reduction of uncertainty and the introduction of new technologies, and how to assess the impact of changes in products throughput and product mix. The methodology is illustrated with an example derived from an actual application in the semiconductor industry.     

Judicious order acceptance and order release in make-to-order manufacturing systems

This paper explores a two-stage input control system for fixed capacity make-to-order manufacturing systems (with heavy job tardiness penalties), that selectively accepts incoming orders and holds the accepted ones in a pre-shop queue prior to releasing them to the shop floor. Single-stage input control systems that only allow orders to be delayed in a pre-shop queue (i.e. they do not allow some orders to be rejected) have been previously investigated and found to negatively impact overall due-date performance. The hypothesis motivating this research is that judiciously rejecting a subset of incoming orders can prevent the order release queue from being overloaded when a surge of demand occurs. The input control system is evaluated via experiments using a discrete-event simulation model of a fixed capacity manufacturing system. The experiments reported here suggest that holding orders in the pre-shop queue does not improve due date performance, and that judiciously rejecting orders on its own is a viable alternative mechanism of input control that can deliver improved performance.     

A heterarchical generic discrete manufacturing simulation model and its application in a world class manufacturing environment

Current factory design and evaluation is very primitive. Factory components are designed in many cases independently. Product and process design are not well integrated. An encompassing framework is needed for iterating through a series of total factory designs, searching for optimal performance. In addition, a vehicle is needed for predicting the performance of a proposed advanced manufacturing system, so that engineers may have a sound means for evaluating such proposals. A heterarchical discrete manufacturing SIMNET II simulation model (SIMCELLS) was developed as a comprehensive methodology for designing and evaluating discrete manufacturing systems. SIMCELLS allows manufacturing systems engineers to experiment with alternative system structures and control strategies while seeking that combination of design features that will produce the desired overall system performance. The model in combination with a modernization programme is enabling a firm to successfully manufacture and sell trucks meeting international standards. The SIMNET II model     

Uncertainty,Flexibility Gap and Labour Demand in the Italian Economy

In this paper we analyse the effects of changes in the degree of uncertainty of the economic system and in the “flexibility gap”, deriving from the combined evolution of the degrees of uncertainty and flexibility of the economic system (in particular, labour market flexibility), on regular and irregular labour demand. On the basis of a simple qualitative model, we give a partial interpretation of some stylized facts of the Italian economy during the last decades. We argue that the low uncertainty and flexibility gap in the 1950s and 1960s, their remarkable increases in the 1970s, their inadequate reduction in the 1980s and the new increase of uncertainty and flexibility gap in the first half of the 1990s, have had a considerable influence on the quantity and quality of the “investment in employment” of Italian economy. The higher degree of uncertainty and the inadequate degree of flexibility of the Italian economic system are likely to have contributed towards the lower regular employment rate, compared to the main industrialized countries, and to high irregular employment. An adequate economic policy for reducing the uncertainty of the economic system together with a structural economic policy for increasing the flexibility of the economic system (in particular, an active labour policy for increasing the flexibility of the labour market), would be likely to produce positive effects on the quantity and quality of labour demand, contributing towards reducing unemployment.     

An aggregate production planning framework for the evaluation of volume flexibility

Flexibility in manufacturing has been identified as one of the key factors to success in the marketplace. Many types of flexibility have been identified in the literature among which volume flexibility is one of the most important. Volume flexibility of a manufacturing system is defined as its ability to be operated profitably at different overall output levels. Volume flexibility permits a manufacturing system to adjust production upwards or downwards within wide limits. In this paper, we develop an aggregate production planning model for volumeflexible production systems. The model can be used with a Monte Carlo simulation to evaluate the optimal level of investment in volume flexibility for a firm operating under a given set of market conditions. In addition, the model can be used to develop some conclusions about the relationship between the value of volume flexibility and the cost of holding inventory, the cost of shortage, forecast accuracy, and the length of the planning horizon.     

Flexible reasoning using sensible agent-based systems: A case study in job flow scheduling

Planning and control systems for highly dynamic and uncertain manufacturing environments require adaptive flexibility and decision-making capabilities. Modern distributed manufacturing systems assess the utility of planning and executing solutions for both system goals (e.g. minimize manufacturing production time for all parts or minimize WIP) and local goals (e.g. expedite part A production schedule or maximize machine X utilization). Sensible Agents have the ability to alter their autonomy levels to choose among a set of decision models in order to handle the differences between local and system goals. In this paper, Sensible Agents are applied to a production planning and control problem in the context of job shop scheduling and decision model theory. Sensible Agents provide for trade-off reasoning mechanisms among system and local utilities that are flexible and responsive to an agent's abilities, situational context and position in the organizational structure of the system.