Kazem Abhary

A genetic algorithm based cell design considering alternative routing

Abstract This paper describes a method for simultaneous arrangement of part families and machine cells for cellular manufacturing systems. A unique feature of the proposed method is that it takes into account the relevant production data such as production volume, alternate routings and process sequences. It also has the ability to select the best alternative routing in terms of cell formation for each part before attempting to cluster the machines and the parts. The formation of the part families and the machine cells has been treated as a minimization problem according to a defined cost function. A genetic algorithm is then developed for solving the minimization problem. Two examples are presented to illustrate the usefulness of the proposed method. The strength of this method lies behind its independence from initial conditions and type of objective function.

A genetic algorithm for the optimisation of assembly sequences

This paper describes a Genetic Algorithm (GA) designed to optimise the Assembly Sequence Planning Problem (ASPP), an extremely diverse, large scale and highly constrained combinatorial problem. The modelling of the ASPP problem, Which has to be able to encode any industrial-size product with realistic constraints, and the GA have been designed to accommodate any type of assembly plan and component. A number of specific modelling issues necessary for understanding the manner in which the algorithm works and how it relates to real-life problems, are succinctly presented, as they have to be taken into account/adapted/solved prior to Solving and Optimising (S/O) the problem. The GA has a classical structure but modified genetic operators, to avoid the combinatorial explosion. It works only with feasible assembly sequences and has the ability to search the entire solution space of full-scale, unabridged problems of industrial size. A case study illustrates the application of the proposed GA for a 25-components product.

Assembly sequence planning and optimisation using genetic algorithms: Part I. Automatic generation of feasible assembly sequences

Abstract This paper attempts to formalise, solve and optimise (S/O) the Assembly Sequence Planning Problem (ASPP), a large scale, highly constrained combinatorial problem. Due to the complexity of the subject and the number of related matters to be considered/adapted/solved prior to S/O the ASPP, the paper is split in two, self-contained, parts: Part I—Automatic Generation of Feasible Assembly Sequences and Part II—optimisation of assembly sequences using Genetic Algorithms. The first part deals with formalising the ASPP—modelling and representation issues—and generating feasible assembly sequences (solving the ASPP). The second part is concerned with the optimisation of the ASPP and will present in detail the Genetic Algorithm designed to optimise it, the genetic operators that compose the algorithm and the definition of the fitness function (optimisation function). The ASPP is considered here as a full-scale, unabridged problem.

A fuzzy integrated decision-making support system for scheduling of FMS using simulation

Abstract In the complex environment of an automated manufacturing system, decision-making is one of the most important and difficult tasks of a manager in general or a scheduler in particular. Flexible Manufacturing Systems (FMSs) are highly automated and expensive systems. The high investment cost of a FMS justifies the use of computer simulation support. This paper investigates the operational problems of FMSs through simulation, and different combinations of scheduling rules are evaluated by a fuzzy integrated decision-making support system.

Knowledge-based tool for planning of enterprise resources in ASEAN SMEs

Abstract Manufacturing has been identified as a key pillar of growth in many Southeast Asian (ASEAN) economies. However, in the last decade many countries have become keen competitors for foreign direct investments. Many countries are trying to improve their total business capabilities by encouraging computerisation of small and medium sized enterprises (SME). Manufacturing SMEs (M-SMEs) are tasked to adopt technologically advanced programmes. With an improving public education system and more literate work force, more SMEs are better positioned to tap into the knowledge-based economy. There is tremendous amount of knowledge intensive activities within the multi-flows of the M-SMEs. Although the concept of ERP systems and artificial intelligence (AI) techniques have been around for more than two decades, this has largely remained the domain of the larger companies. ASEAN M-SMEs have been slow to implement it. In this paper, the various strategic and operational requirements of regional M-SMEs are presented and a knowledge-based resources planning model making use of AI techniques is proposed. This improved AI model makes use of the large amount of accumulated knowledge typically found in the M-SMEs, especially those in the electronics and precision engineering sectors. This includes a case study of how an electronics precision engineering company adopted the proposed AI model.

Design and evaluation of automated cellular manufacturing systems with simulation modelling and AHP approach: a case study

Suggests that many quantitative methods have been developed in an attempt to acknowledge uncertainty in decision making and to manage the inherent risk during economic planning for new technology implementation. Outlines a relatively simple and practical risk analysis, accompanied by the implementation of advanced manufacturing technology. Employs the proven analytical hierarchy process (AHP) approach, coupled with confidence intervals from data gathered through simulation techniques or through observations and empirical sampling. Describes a case study in which simulation models were developed using a software package SIMFACTORY II.5, which is based on the concept of visual interactive simulation. A number of simulation experiments were performed in order to investigate the influence of various flexible manufacturing system and cellular manufacturing system configurations. An AHP multi‐attribute analysis is performed by using AUTOMAN, a decision support software package. This package evaluates and combines the qualitative and quantitative factors for different configuration designs.

A fuzzy approach to operation selection

Abstract Production management and scheduling problems inflexible manufacturing systems (FMSs) are complicated, compared with those problems in job shops and transfer lines. Due to the flexibility of FMSs, alternative operations are common. This paper presents a fuzzy approach to operation and routing selection via simulation. The rule developed here is compared with some other well-known conventional rules like WINQ (work in queue) and SNQ (shortest number of jobs in queue).

A decision support system for cellular manufacturing system design

With the growth of competitive pressure in the global markets, there has been an increase in demand in industry for cellular manufacturing systems (CMSs) in order to improve productivity and process flexibility. The design of CMSs for industrial applications is a complex and knowledge intensive process as it involves the consideration of many factors including production data and process characteristics. This paper describes the development and implementation of a decision support system for the feasibility and conceptual design of CMSs. The system is based on the knowledge-based system approach, and is able to make recommendations of system feasibility, cell formation techniques and cell types. A case study is also presented to demonstrate the capability of the decision support system.

Optimisation of partner selection and collaborative transportation scheduling in Virtual Enterprises using GA

Partner selection and transportation scheduling are critical to the success of a Virtual Enterprise. Collaborative transportation is a promising strategy that can help many enterprises survive and thrive in todays highly competitive market. To help decision makers establish and operate Virtual Enterprises more effectively, an innovative decision support system is proposed in this paper. First, new model for integration of partner selection and collaborative transportation scheduling in Virtual Enterprises is developed. This integrated optimisation problem is very dynamic in nature and it is required to optimise a number of interlinked sub-problems at the same time. Then, a novel Genetic Algorithm with a unique dynamic chromosome representation and genetic operations is developed to find an optimal solution to the integrated problem. The effectiveness of the proposed approach is demonstrated in a representative case study.

Development of a multiattribute synthetic-np chart

Over the last few decades, multiattribute control charts have been widely recommended in practice. They outperform the simultaneous uniattribute charts for monitoring multiattribute processes in many applications. Jolayemi [A statistical model for the design of multiattribute control charts. Indian J Stat. 1999;61:351–365] developed a statistical model for the design of a multiattribute np (Mnp) chart. Based on this model, a multiattribute synthetic (MSyn) chart is proposed in this article. Furthermore, the main features of the MSyn chart and Mnp chart are integrated to build a multiattribute Syn-np (MSyn-np) chart. The results of the comparative studies indicate that the new MSyn-np chart significantly outperforms the Mnp chart and MSyn chart by 83% and 27%, respectively, in terms of the average number of defectives over a wide range of process shifts under different circumstances.