Cellular Versus Functional Layouts Under a Variety of Shop Operating Conditions*

This paper addresses the suitability of cellular manufacturing under a variety of operating conditions. Queueing theoretic and simulation models of cellular and functional layouts are developed for various shop operating environments to investigate several factors believed to influence the benefits associated with a cellular manufacturing layout. The queueing models show how operations overlapping, which is more practical with a cellular layout, becomes more beneficial as the lot size increases. The simulation models are developed to study the performance of cellular and functional layouts in a wide variety of operating environments by varying the levels of four factors: (1) the degree to which natural part families occur, (2) the number of operations required to process the parts, (3) the processing times of the parts at each machine, and (4) the lot size. Two response variables are used to measure shop performance: the average time spent by a batch in the system, and the average work-in-process level. Statistically significant reductions in the average time in the system and average work-in-process measures were detected for the cellular layouts in all the operating environments studied.     

Applications and Implementation: AN EXPERIMENTAL COMPARISON OF CELLULAR (GROUP TECHNOLOGY) LAYOUT WITH PROCESS LAYOUT

This study compares different strategies for arranging machines in a facility. Computer simulation of two different machine shops was used to compare process layout (the arrangement of groups of machines where the machines within a group are interchangeable) to cellular layout designed using group technology concepts (the use of manufacturing cells where each cell contains different types of machines dedicated to the production of similar parts). Four layout strategies, including process layout, cellular layout, and two hybrid layouts, were compared in two machine-shop models. The shops that used cellular layouts had shorter setup times, lower machine utilization, and shorter distances traveled, on average. The shops with process layout, however, had better performance on queue-related statistics such as work-in-process inventory level and average flow time. This suggests that a well-organized traditional job shop may be able to achieve overall performance that at least is comparable to that of the same shop using cellular (group technology) layout.     

Alternate Routing Strategies in Batch Manufacturing: An Evaluation

Batch manufacturing firms are experiencing significant changes because of technological developments in work center design, such as flexible manufacturing systems (FMS) and planning/control tools like computer-aided process planning (CAPP). These new developments provide production managers with some solutions to a number of complex problems. For example, numerical-controlled (NC) machine center installations are effective in providing quality parts because of tight tolerance specifications built into the equipment. However, these highly efficient centers create bottlenecks that constrain shop throughput, since production planners tend to rely too much on them. To help improve manufacturing planning, we introduce an important element to the batch production scheduling component of CAPP's mission—evaluating possible alternate routes. Production scheduling encompasses job route selection as well as machine center assignment (loading), job releasing, and setting due dates. In this paper, three routing strategies requiring different levels of shop floor information are tested and evaluated using computer simulation. Shop performance is measured by total cost and traditional measures of job flow time, lateness, and tardiness.     

A simulated annealing algorithm for designing cellular manufacturing systems with productivity consideration

In this paper, we propose a productivity model for solving the machine-part grouping problem in cellular manufacturing (CM) systems. First, a non-linear 0-1 integer programming model is developed to identify machine groups and part families simultaneously. This model aims to maximize the system productivity defined as the ratio of total output to the total material handling cost. Second, an efficient simulated annealing (SA) algorithm is developed to solve large-scale problems. This algorithm provides several advantages over the existing algorithms. It forms part families and machine cells simultaneously. It also considers production volume, sales price, and maximum number of machines in each cell and total material handling cost. The proposed SA also has the ability to determine the optimum number of manufacturing cells. The performance of the developed models is tested on eight problems of different size and complexity selected from the literature. The results show the superiority of the SA algorithm over the mathematical programming model in both productivity and computational time.     

An approachto the machine layout problem in a cellular manufacturing environment

The model of the machine layout problem MLP in a cellular manufacturing environment attains additional dimensions as it should satisfy the qualitative interconnections between the machines and the location restrictions of an existing factory environment. A new MLP model based on merging pre-emptive goal programming and simulated annealing has been developed for machine layout in cells. This model seeks to find feasible solutions by addressing practical issues of implementation as well as reducing the total travel distances for parts between machines. The new model can also be applied to facility layout problems FLP . The computational work is demonstrated by applying the model to problems of both quantitative and qualitative types, and has produced encouraging results. This model is particularly attractive for layout problems with realistic goals and constraints. To show the performance of the model in handling real-world problems, a practical example has been introduced and solved using the proposed model.     

Shop Performance Implications of Using Cells,Partial Cells,and Remainder Cells*

This paper considers the application of cellular manufacturing (CM) to batch production by exploring the shop floor performance trade‐offs associated with shops employing different levels of CM. The literature has alluded to a continuum that exists between the purely departmentalized job shop and the completely cellular shop. However, the vast majority of CM research exists at the extremes of this continuum. Here, we intend to probe performance relationships by comparing shops that exist at different stages of CM adoption. Specifically, we begin with a hypothetical departmentalized shop found in the CM literature, and in a stepwise fashion, form independent cells. At each stage, flow time and tardiness performance is recorded. Modeling results indicate that, depending on shop conditions and managerial objectives, superior shop performance may be recorded by the job shop, the cell shop, or by one of the shops between these extreme points. In fact, under certain conditions, shops that contain partially formed cells perform better than shops that use completely formed cells. Additional results demonstrate that in order to achieve excellent performance, managers investigating specific layouts need to pay especially close attention to changes in machine utilization as machine groups are partitioned into cells.     

ON THE RELATIVE PERFORMANCE OF FUNCTIONAL AND CELLULAR LAYOUTS- AN ANALYSIS OF THE MODEL-BASED COMPARATIVE STUDIES LITERATURE

Paralleling the increased interest in cellular manufacturing in recent years, a large number of studies have emerged that focus on the relative performance of cell systems and the functionally organized systems they replace. This paper is an analysis of studies that use model-based, controlled experimentation to seek answers to the questions of if, when, and why cellular layouts outperform their functional counterparts. Twenty-four model-based studies are analyzed with respect to their definitions of cellular versus functional layouts, the experimental factors that have been investigated, the results concerning relative performance, and the findings' relevance to layout choice. We conclude that although the comparative studies have been very valuable in their efforts at identifying the factors that embody the essence of cells and shape performance improvements, most of the basic findings are known from past research. Furthermore, the studies' findings cannot assist practitioners in making specific choices between existing layouts and alternative cell systems. However, the totality of the findings reinforce our knowledge of how work systems in general can be designed and organized to reduce throughput time, and can also be used to identify environments and conditions for which conversions to cells may have more or less potential.     

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.     

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。     

Lead time adjustment through scrap management

In a discrete parts manufacturing environment, it is necessary to compensate for the decreasing planned batch size resulting from production of scrap (defectives) in the production line, by increasing the planned production volume. This calls for a revision in the initially computed manufacturing lead time (MLT). A survey of the literature reveals that although issues related to product quantity regeneration have been studied in detail, little has been done to assess the impact on manufacturing lead times. This paper discusses the impact of scrap on manufacturing lead time in a shop with an intermittent-flow, bath-oriented, discrete-parts manufacturing environment, producing make-to-stock items.     

面向并行制造的多生产单元协同调度研究

为提升多生产单元制造系统整体效率，在其系统内开展面向并行制造的协同调度研究，在考虑运输、换线等时间的基础上，构建多生产单元并行协同调度模型，采用并行分段协同遗传算法求解；在此基础上，将所研究协同调度方法应用于某复杂机电产品多生产单元制造车间，并与变批量调度与等批量调度比较。研究表明，所提的并行协同调度方法可以显著提升生产单元效率，提高生产单元设备和人员利用率。     

A Study of Labor Allocation Strategies in Cellular Manufacturing

Current research studies in cellular manufacturing have considered environments constrained only by the machine resource, when in fact the flexibility of manufacturing cells is derived mainly from its allocation of the labor resource. This research specifically examines the labor resource in cellular manufacturing, also known as group technology (GT), through a series of simulation experiments on a hypothetical GT shop and recommends conditions under which different labor allocation strategies may be appropriate. The effects of various product routings and scheduling policies on labor allocation are also examined.     

A DISCRETE PRODUCTION SWITCHING RULE FOR AGGREGATE PLANNING

Aggregate planning (AP) is a necessary activity for manufacturing and services alike. A shift toward high-volume batch and continuous flow processes within American manufacturing has given rise to increasing numbers of crew-loaded facilities. A majority of AP approaches incorporate continuous decision variables and require frequent adjustments to both production and work-force settings. Despite the availability and diversity of these approaches, few significant applications have been reported. This paper presents the detailed development of a discrete AP switching rule that can be applied to a variety of cost environments. Inventory costs are estimated using an interval approach rather than traditional point estimates. The model allows incorporation of overtime options and is interactive in nature. Decision variables from the model can be disaggregated and linked directly to lower-level planning activities. Actual results of model implementation are reported. An overview of the model's incorporation into the larger context of hierarchical production planning is found in [21].     

An evaluation of product commonality and group technology production methods in a pre-defined multiple-machine scenario

Group technology has been used successfully for a number of years as a setup reduction tool. It is especially valuable in low-volume high-mix manufacturing environments where products and machines may be partitioned into product families and machine cells. The partitioning of machines or processes into cells may be limited by practical constraints, and the partitioning of products is complicated as the number of products and processes increases. In this paper, the authors examine the behaviour of various grouping strategies lauded as being appropriate in situations where machine partitioning and product routeing are determined by technological constraints. Of specific experimental concern in this paper is the effect of the mean and variance of component part commonality between products on system performance under various grouping strategies in a multiple-machine environment.     

Processing in a multi-machine batch manufacturing system with sequence dependent cost

Many workcells in batch manufacturing systems are populated with multiple, nonidentical machines that perform similar tasks. Because of the size of a batch when a job arrives, it may be uneconomical to set up two or more machines to process the same job simultaneously. An economic decision has to be made as regards which machine in the cell to assign the job. Likewise, many multi-operation jobs can be processed using one of several feasible operation sequences that may lead to different total manufacturing costs. The cost differences are the result of several factors, among which are processing time and cost dependencies between operations, fixturing requirements, and material handling requirements. When the workcell machine selection decision is considered along with the operation sequencing decision, determination of the best machine in a cell and the best operation sequence for the batch is a non-trivial task. In this paper, we address the problem of selecting the best machine within a cell and the best operation sequence for a batch when operation cost is machine and sequence dependent. The problem is modeled mathematically and solved using a heuristic algorithm. The performance of the algorithm is compared with that of an exact solution procedure.     

A modified hierarchical production planning system integrated with MRP: A case study

In this paper, a hierarchical planning system is proposed which integrates aggregate capacity planning with MRP. This system is to be implemented in a metal box manufacturing company which multi-user MRP system covering manufacturing activities as well as procurement sales order processing and accounting systems. The hierarchical planning system includes a medium-range aggregate planning model adapted to the firm's requirements and strategies. The model consists of a mathematical formulation which covers labour capacity has already installed a constraints and includes certain cost estimations in the objective function. The planning horizon of the medium range planning is taken as twelve months in order to cover sales seasonality. The aggregate production quantities resulting from the optimized medium-range planning model are disaggregated according to procedures already found in the literature. Furthermore, the theoretical infeasibilities pertaining to the disaggregation procedures are also resolved in an heuristic manner. Using the latter modified disaggregation procedure, a feasible disaggregated plan is generated for the whole planning horizon. The proposed plan is compared with the current production policy of the firm and it is observed that the proposed plan leads to backorder reduction.     

A neural network clustering model for miscellaneous components production planning

The growing importance of providing service to customers, e.g. post-sale assistance, supplying of spare parts, upgrading and integration of new elements in installed systems, enhances the importance of planning and management of upgrading parts in most manufacturing industries. These parts are generally characterized by high technical heterogeneity and have a highly variable and difficult to forecast demand. In some areas (especially the most dynamic, e.g. high-tech products), these kinds of components are quite common, and represent a very strong relation between the manufacturing firm and the market. These parts are generally too many to be efectively supported on a planning database system with individual records and too heterogeneous ( and sometimes with a too high value) to be supported all together in a single record. In this paper, we want to study the application of adaptive techniques for the clustering of these components in classes based on the similarities in their market behaviour in order to build an optimal database for planning production and supplying of these components.     

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.     

Period batch control: Classic,not outdated

Period Batch Control was developed and first applied during the Second World War. The historic roots are discussed and the principles of this classic production planning approach explained, PBC compared to other production control concepts, and it is demonstrated that it may still be fruitfully applied, especially in combination with cellular manufacturing. It is therefore considered as a classic, but not outdated production planning concept.     

Scheduling in an assembly-type production chain with batch transfer

This paper addresses a three-machine assembly-type flowshop scheduling problem, which frequently arises from manufacturing process management as well as from supply chain management. Machines one and two are arranged in parallel for producing component parts individually, and machine three is an assembly line arranged as the second stage of a flowshop for processing the component parts in batches. Whenever a batch is formed on the second-stage machine, a constant setup time is required. The objective is to minimize the makespan. In this study we establish the strong NP-hardness of the problem for the case where all the jobs have the same processing time on the second-stage machine. We then explore a useful property, based upon which a special case can be optimally solved in polynomial time. We also study several heuristic algorithms to generate quality approximate solutions for the general problem. Computational experiments are conducted to evaluate the effectiveness of the algorithms.