Implementation Of Cellular Manufacturing Systems Research Articles

An integrated approach to modelling of barriers in implementation of cellular manufacturing systems in production industries

An integrated approach to modelling of barriers in implementation of cellular manufacturing systems in production industries

Modelling and analysis of enablers for successful implementation of cellular manufacturing system

The primary objective of this paper is to develop a model for the enablers supporting the implementation of cellular manufacturing systems with the help of interpretive structural modelling methodology. These enablers were dissected through literature review and expert's opinion. The questionnaire-based review has been accomplished for the ranking of these enablers. The MICMAC analysis has been performed to interpret the mutual dependencies of 'driving enablers' (i.e., which help to accomplish other enablers) and 'dependent enablers' (i.e., which are accomplished by driving enablers). From the outcomes, it has been observed that improved production process stability and capability, increased automation, and improved worker skill flexibility forms lowest level in the ISM hierarchy. These enablers have high driving power and low dependence power. So, these enablers may be treated as the 'key enablers'. These key enablers would avail the management in contributing appropriate supervision and guidance during the successful implementation of cellular manufacturing system.

Identification of key barriers affecting the cellular manufacturing system by ISM approach

The cellular manufacturing (CM) has been proved as a well-known manufacturing strategy that helps to improve manufacturing efficiency and productivity by utilising the philosophy of group technology. Cellular manufacturing (CM) has emerged as a strong approach for improving operations in batch and job shop environments. In cellular manufacturing, group technology is used to form part families based on similar processing requirements. Cellular manufacturing systems (CMSs) are those systems which are capable to meet the requirements of modern manufacturing industries. But adoption and implementation of CMSs is not an easy task. There are certain barriers which not only influence the implementation process but also influence each other. The main objective of this paper is to identify and analyse these barriers. In the present work, these barriers have been identified through the literature, their ranking is done by a questionnaire-based survey and interpretive structural modelling (ISM) approach has been utilised in analysing their mutual interaction.

A hybrid multi-objective approach based on the genetic algorithm and neural network to design an incremental cellular manufacturing system

One important issue related to the implementation of cellular manufacturing systems (CMSs) is to decide whether to convert an existing job shop into a CMS comprehensively in a single run, or in stages incrementally by forming cells one after the other, taking the advantage of the experiences of implementation. This paper presents a new multi-objective nonlinear programming model in a dynamic environment. Furthermore, a novel hybrid multi-objective approach based on the genetic algorithm and artificial neural network is proposed to solve the presented model. From the computational analyses, the proposed algorithm is found much more efficient than the fast non-dominated sorting genetic algorithm (NSGA-II) in generating Pareto optimal fronts.

An Electromagnetism-like algorithm for cell formation and layout problem

Implementation of cellular manufacturing systems (CMS) is thriving among manufacturing companies due to many advantages that are attained by applying this system. In this study CMS formation and layout problems are considered. An Electromagnetism like (EM-like) algorithm is developed to solve the mentioned problems. In addition the required modifications to make EM-like algorithm applicable in these problems are mentioned. A heuristic approach is developed as a local search method to improve the quality of solution of EM-like. Beside in order to examine its performance, it is compared with two other methods. The performance of EM-like algorithm with proposed heuristic and GA are compared and it is demonstrated that implementing EM-like algorithm in this problem can improve the results significantly in comparison with GA. In addition some statistical tests are conducted to find the best performance of EM-like algorithm and GA due to their parameters. The convergence diagrams are plotted for two problems to compare the convergence process of the algorithms. For small size problems the performances of the algorithms are compared with an exact algorithm (Branch & Bound).

A hybrid approach based on the genetic algorithm and neural network to design an incremental cellular manufacturing system

One important issue related to the implementation of cellular manufacturing systems (CMSs) is to decide whether to convert an existing job shop into a CMS comprehensively in a single run, or in stages incrementally by forming cells one after the other, taking the advantage of the experiences of implementation. This paper presents a new nonlinear programming model in a dynamic environment. Furthermore, a novel hybrid approach based on the genetic algorithm and artificial neural network is proposed to solve the presented model. From the computational analyses, the proposed algorithm is found much more efficient than the genetic algorithm and simulated annealing in generating optimal solutions.

A New Approach to Fuzzy Part-Family Formation in Cellular Manufacturing Systems

Group technology (GT) is one of the major issues in successful implementation of cellular manufacturing systems. The success of GT implementation depends only on an effective formation of part-families. The effective formation of part-families depends mainly on an effective formation of a similarity coefficient measure. Many similarity coefficients have been produced over the past three decades, but better similarity coefficient measures are required. The decision-making process in a manufacturing system often involves uncertainties and ambiguities. Under such circumstances, fuzzy methodologies have proved to be effective tools for taking fuzziness into consideration. In this paper, we use fuzzy cluster analysis to form part-families and assign parts to existing part-families. We have established a new approach to convert a fuzzy clustering matrix into a zero-one incidence matrix. We have also developed a new similarity coefficient measure and this coefficient measure is used to form a part-family. A mathematical model that uses this similarity coefficient for solving optimally the part-family formation problems in cellular manufacturing is developed. Finally, it is compared with other models by giving an illustration with a numerical example.

Experiences of a small to medium size enterprise in the design and implementation of manufacturing cells

Small and medium size enterprises (SMEs) have gained competitive advantage by using Just-in-Time, Total Quality Management, and Information Technology. Cellular Manufacturing (CM) has received less attention from SMEs. This paper reports the findings of a case study of the application of Group Technology in an SME. A framework for the design and implementation of Cellular Manufacturing Systems (CMSs) is proposed. The framework is examined and explained in the context of the case study. The first part of the paper examines the nature of CM as well as its strategic value to manufacturing firms. The second part focuses on the design and implementation of CMSs. The third part presents a framework for the design and implementation of CMSs. Finally, a case study conducted at a small company in England is used in demonstrating the application of the framework.

A simulator-based approach to cellular manufacturing system design

Cellular Manufacturing (CM) is a product-oriented organizational strategy that is recognized as one of the critical elements in the rejuvenation of outdated and unproductive manufacturing plants. Successful planning, design, and implementation of Cellular Manufacturing Systems (CMS) require the development of sound, replicable system design approaches. In this paper, a simulator-based approach for the design of manufacturing cells and systems is described. The approach utilizes holistic systems design concepts and addresses Hitomi's three fundamental aspects of manufacturing systems: transformational, procedural, and structural. A distinction is made between system logic and system structure and the concepts of logical design and physical design are utilized. The approach described can assist the designer by providing a systematic holistic methodology to the CMS design process.