The human factor in cellular manufacturing

The role of Feasibility Assessment (FA) is critical for Cellular Manufacturing (CM) that based on Group Technology (GT) concept, particularly during the design phase. The results may be used in decision making process to decide whether or not job shop may be converted into CM. Through FA some procedures are followed to identify the right predicted cells number that leads to create effective CM. In this article two methods of predicting a number of cells have been examined. The first method is supported by the number of machines in the incidence matrix and the pre-determinable maximum number of machines in each machine cell. The second method was based on Rogers and Tanimoto Similarity Coefficient and Eigenvalues of the Similarity Coefficient Matrix. Ten data sets selected from literatures are used to test these two methods. The results show that the first method is less accurate, depends on trial and error, and has multi values where most of those values are not integers. On the contrary, the second method is very accurate, has only one solution which is an integer value. Therefore it may be considered as a more efficient method. Furthermore, this study suggested an efficient and logical sequence of these two methods in order to identify the performance of the existing methods that are used in solving cell formation problems.A Comparative Study on Predicting Methodsfor Cell Formation Problem

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.

Group technology (GT) seeks to exploit similarities among parts or products for efficiencies in design and manufacturing. Production Flow Analysis (PFA) seeks to exploit similarities in processes. Applications of GT in Computer Aided Process Planning (CAPP), and GT and PFA in cellular manufacturing (CM) have produced very significant, and well-publicized productivity improvements compared to traditional methods; yet a vast majority of firms are yet to use them.

Cellular Manufacturing (CM) is an important application of Group Technology (GT) in which families of parts are produced in manufacturing cells or a group of various machines, which are physically close together and can entirely process a part family. The manufacturing system established based on such an idea is called Cellular Manufacturing System (CMS). A major problem associated with many CMSs is the existence of Exceptional Elements (EEs), i.e. bottleneck machines and exceptional parts. These are machines/parts that cannot be exclusively assigned to a machine cell/part family. In this paper a new model is presented for dealing with the EEs in the form of a Multi-objective Optimization Problem (MOP). This model aims to minimize: (1) intercellular parts movements, (2) total cost needed for machine duplication and part subcontracting, (3) the system's under-utilization, and (4) deviations among the cells' utilization. Attaining an ideal solution, which is optimal to all of the objectives is prohibited, as they conflict with each other. Hence, a Multi-Objective Genetic Algorithm (MOGA) is developed to provide the decision-maker with a set of non-dominated or Pareto-optimal solutions. Comparisons between the developed MOGA and three other MOGAs show its viability in three performance aspects, namely: quality, diversity and CPU time.

Performance of hybrid cellular manufacturing systems: A computer simulation investigation

A capacity constrained mathematical programming model for cellular manufacturing with exceptional elements

Group technology (GT) is a manufacturing philosophy which identifies and exploits the similarity of parts and processes in design and manufacturing. A specific application of GT is cellular manufacturing (CM). The first step in the preliminary stage of cellular manufacturing system (CMS) design is cell formation, generally known as a machine-part cell formation (MPCF) or a machinecomponent grouping (MCG) problem. Simulated annealing (SA) is not only a highly effective and general random search method to obtain near-global optimal solutions for optimization problems, but also quite appropriate for the MPCF problem which is an NP complete, complex problem. In this study, we introduce modified SA with the merits of a genetic algorithm (GA), call parallel SA (PSA), and propose a PSA-based procedure to solve the MPCF problem. More specifically, this study aims to minimize (1) total cost which includes intercell and intracell part transportation cost and machine investment cost, (2) intracell machine loading unbalance and (3) intercell machine loading unbalance under many realistic considerations. The illustrative example, comparisons and analysis demonstrate the effectiveness of this procedure. The proposed procedure is extremely adaptive, flexible, efficient and can be used to solve real MPCF problems in factories by providing a robust manufacturing cell formation in a short execution time.

The importance of the planning and distribution of machines in a plant determines the efficiency of the work and, possibly, the survival of the company, but we found that the reality of many Latin American companies is that they have within their facilities, a physical disorder of the productive elements, which leads to an inadequate use of materials and personnel, and a poor performance of their operations. Within this framework, a study was developed based on a systematic review of the "manufacturing cell". The manufacturing cell or also called work cells, is a valuable tool of Lean Production, which focuses on cellular manufacturing, characterized by a distribution of machines, where each cell can be composed of one or several different machines, which perform certain tasks associated with the manufacture of a family of products with similar characteristics, having the great opportunity for many Latin American companies to raise efficiency, working with individual cells, this would allow to manufacture parts and components with high precision and quality, and covering the needs of the market. In the present study 56 studies were collected, identifying that 59% belong to scientific articles and 41% are university theses, having as database Scielo, Proquest, EBSCO, Dialnet, Google Scholar, Engineering Source, Scopus and Renati. The review of the scientific literature concerned the industrial sector, finding the implementation of "manufacturing cells", for example, in the textile company BROOKLYN S.R.L, which achieved a decrease in unproductive time of transfer from one machine to another, generating a man-hour productivity of 16% in men's pants, and in women's models with 34% and 102% according to their classes. Another example is the one carried out in the company Ipsycom Ingenieros S.R.L., which achieved an increase in productivity in 70% of the clothing in general, in addition to improving communication between workers, reducing the time between the order and delivery, and reducing the inventory of work.

Cellular manufacturing represents an effective and even more applied alternative in production system organization especially when line or batch-type production is not economically convenient or technically feasible. This is particularly true when a wide range of quite similar items need to be produced in small lot sizes with frequent and expensive setups. Cellular manufacturing is supported by the so-called cell formation problem whose aim is forming part groups to be assigned to manufacturing cells, composed by a defined subset of machines, so that the sum of intercellular flow costs and direct intra-cell costs is minimized. An effective approach to form manufacturing cells is based on cluster analysis and on the evaluation of similarity coefficients: machines are grouped by the application of clustering techniques and finally parts are assigned to clusters. The aim of this paper is to present a hybrid and original procedure for the cell formation problem based on cluster analysis and integer linear programming. In particular, an integer linear programming model optimizes and re-arranges the configuration of the cells as the result of the application of a hierarchical clustering algorithm. The proposed model evaluates the possibility of duplicating a machine in one or more cells in order to reach the best trade-off between direct cell costs and indirect costs caused by intercellular flows. As a result, all work areas are correctly designed with the optimal number of machines of each type and total production system cost is quantified. The presentation and discussion of the proposed approach is supported by the illustration of a significant case study which takes inspiration from the literature.

Group technology (GT) utilizes a philosophy that involves grouping of components having similarmanufacturing and design attributes , known as part families (PF). In a job shop (JS) products are processedin smaller batches and with the products are changed the new processing sequence increases /changesmaterial handling within JS. Hence to reduce material handling machines need to be arranged in cells so thatmost of family members can be manufactured within the cell referred as Cellular manufacturing (CM), whichis one of the application of GT . The main goal of this research work is to present a performance comparison offunctional JS of small medium enterprise (SME) with the objective to decrease intracellular movement of partsusing newly developed approach. Effectiveness of reconfigured JS due to the proposed method and thefunctional layout is compared using six well known measures.DOI: http://dx.doi.org/10.3329/jme.v43i2.17829

Organisations willing to succeed in global competition have to integrate their internal and external processes. This especially includes planning and production control (PPC) processes. Optimised allocation of the production resources and quick response to demand changes result in lower cost and improvement of production performance. Practitioners and researchers have been trying to achieve these goals using production planning techniques. Although the results are significant, it seems necessary to integrate production operations in order to improve the production performance. The goals, information and decisions taken in production planning and control and process planning are often very different and difficult to integrate in Cellular Manufacturing (CM) environments. Designing an efficient PPC system and integrating it with process planning in a cellular environment is of the same importance. The following paper proposes first a comprehensive framework of integrated process planning and production planning and control in CM. Then, with respect to this framework and utilising the domain knowledge in the area of CM systems, an integrated model based on Integrated Definition Modeling Language is developed. The application of the models has been considered as a case study for a production system in electronics and telecommunication sector in a plant in Iran. The validity and completeness of the proposed model is tested by a panel of experts in the areas of production planning and control in CM environments.

Group technology (GT) offers many advantages to firms engaged in batch manufacturing, including lower setup times, reduced lot sizes, lower lead times, and easier production planning and control. Period Batch Control (PBC) has been proposed in the literature as a simple production planning and control system for a GT environment, based on the choice of a cycle length. Unfortunately, there are no published studies providing guidelines for the choice of an optimal cycle length. In this paper we develop a cost minimization model for examining the choice of cycle length, and demonstrate its use by applying it to four published data sets. The analysis shows that the cell design itself directly affects total inventory and overtime costs and the choice of cycle length; that demand increases can be very expensive for a given cell design; and that the degree of demand uncertainty is an important factor in PBC design. The key managerial consideration is the amount of slack capacity to build into the cell d...

Presents some of the preliminary findings from research which has sought to identify performance drivers in manufacturing cells. A medium‐sized UK automotive component supplier which operates on a JIT basis was used for the research which has also examined the perceived and actual inter‐relationships between cell drivers and the effect of these on goal congruence. The results illustrate a fundamental difference in perception between production manager and the shop floor together with a shared misconception regarding perceived driver interactions. The result is a disjointed performance measurement system which fails to drive the continuous improvement required in the manufacturing cells.

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.

An Anti-Union Corporate Culture and Cell Manufacturing