Environment conscious manufacturing edited by S.M. Gupta and A.J.D. Lambert

The dynamic facility layout problem (DFLP) aims to minimise the sum of handling and re-layout costs by devising an individual layout for each distinctive production period. In this paper, a hybrid particle swarm optimisation (HPSO) algorithm is proposed to find near-optimal solutions of DFLP. We use a coding and decoding technique that permits a one to one mapping of a solution in discrete space of DFLP to a PSO particle position in continuous space. The proposed PSO will further use this coding technique to explore the continuous solution space. For further enhancement, the proposed PSO is hybridised with a simple and fast simulated annealing. The developed algorithm is capable of being extended to more general cases although equal area machines and standardised handling equipments with identical unit costs are assumed for the time being. Computational results show the efficiency of the proposed algorithm compared to other heuristics.     

A genetic algorithm and queuing theory based methodology for facilities layout problem

Facilities layout, being a significant contributor to manufacturing performance, has been studied many times over the past few decades. Existing studies are mainly based on material handling cost and have neglected several critical variations inherent in a manufacturing system. The static nature of available models has reduced the quality of the estimates of performance and led to not achieving an optimal layout. Using a queuing network model, an established tool to quantify the variations of a system and operational performance factors including work-in-process (WIP) and utilisation, can significantly help decision makers in solving a facilities layout problem. The queuing model utilised in this paper is our extension to the existing models through incorporating concurrently several operational features: availability of raw material, alternate routing of parts, effectiveness of a maintenance facility, quality of products, availability of processing tools and material handling equipment. On the other hand, a queuing model is not an optimisation tool in itself. A genetic algorithm, an effective search process for exploring a large search space, has been selected and implemented to solve the layout problem modelled with queuing theory. This combination provides a unique opportunity to consider the stochastic variations while achieving a good layout. A layout problem with unequal area facilities is considered in this paper. A good layout solution is the one which minimises the following four parameters: WIP cost, material handling cost, deviation cost, and relocation cost. Observations from experimental analysis are also reported in this paper. Our proposed methodology demonstrates that it has a potential to integrate several related decision-making problems in a unified framework.     

A two-phase procedure for duplicating bottleneck machines in a linear layout,cellular manufacturing system

We discuss a two-phase procedure for duplicating bottleneck machines in a cellular manufacturing system. Given a preliminary solution by a clustering technique, the first phase solves a cellular layout problem in which it assigns machine-cells to locations to minimize the total inter-cell material handling costs that result from the bottleneck parts. The purpose of this phase is to find an optimal linear layout of cells. The second phase finds the bottleneck machines that need to be duplicated to minimize the costs. A binary (integer) linear programming model is developed in this phase to minimize the total duplication costs and material handling costs (if not duplicated). Finally, a decision is made as to whether a solution with bottleneck machines, or duplication of bottleneck machines to avoid the bottleneck problem is to be accepted. An example is demonstrated to show how such a bottleneck problem in cellular manufacturing is solved.     

An interactive approach to computer aided facility layout

In all manufacturing and service industries the layout of facilities is an important determinant of operating efficiency and costs. Whenever the flow of materials or people is complex, computerized procedures offer the only feasible means of developing and evaluating alternative arrangements.

This paper describes an interactive approach to construction and improvement procedures which utilizes a refresh graphics terminal (IMLAC)linked to a PRIME 400 computer. Input includes projected materials flow, estimates of material handling costs, 2-D templates of machines, etc., and an initial layout which can be either existing, proposed, or constructed using the procedure INLAYT. A heuristic procedure, S-ZAKY, utilizes multi-pairwise facility exchange to develop improved layouts based upon an analysis of materials flow. The improved layout is displayed in detail alongside the initial layout at the graphics terminal together with relevant material handling costs. The user may then accept, reject or modify the improved layout using the light-pen attached to the terminal before proceeding to successive iterations until satisfied. An economic evaluation of the projected savings in material handling costs against costs of relayout may be displayed at each iteration. On completion, a fully documented record including drawings may be obtained for every stage in the. procedure.     

Sharing clearances to improve machine layout

This paper considers a double-row layout problem with shared clearances in the context of semiconductor manufacturing. By sharing some clearances, reductions in both layout area and material handling cost of approximately 7–10% are achieved. Along with minimal clearances for separating adjacent machines, clearances that can be shared by adjacent machines are considered. The shared clearances may be located on either or both sides of machines. A mixed integer linear programming formulation of this problem is established, with the objective to minimise both material flow cost and layout area. A hybrid approach combining multi-objective tabu search and heuristic rules is proposed to solve it. Computational results show that the hybrid approach is very effective for this problem and finds machine layouts with reduced areas and handling costs by exploiting shared clearances.     

A similarity score-based two-phase heuristic approach to solve the dynamic cellular facility layout for manufacturing systems

The dynamic cellular facility layout problem (DCFLP) is a well-known NP-hard problem. It has been estimated that the efficient design of DCFLP reduces the manufacturing cost of products by maintaining the minimum material flow among all machines in all cells, as the material flow contributes around 10–30% of the total product cost. However, being NP hard, solving the DCFLP optimally is very difficult in reasonable time. Therefore, this article proposes a novel similarity score-based two-phase heuristic approach to solve the DCFLP optimally considering multiple products in multiple times to be manufactured in the manufacturing layout. In the first phase of the proposed heuristic, a machine–cell cluster is created based on similarity scores between machines. This is provided as an input to the second phase to minimize inter/intracell material handling costs and rearrangement costs over the entire planning period. The solution methodology of the proposed approach is demonstrated. To show the efficiency of the two-phase heuristic approach, 21 instances are generated and solved using the optimization software package LINGO. The results show that the proposed approach can optimally solve the DCFLP in reasonable time.     

Facilities layout planning based on Fuzzy multiple criteria decision-making methodology

Space requirements for facilities and the activity relationships among these facilities are important factors in determining the design of a facility layout. A facility layout problem is an unstructured decision problem. One of the real difficulties in developing and using models for layout design is the natural vagueness associated with the inputs to the models. The personnel flow rate between different departments should be viewed as vague inputs. The analyst is typically uncertain about what this input should be, yet the formulation requires exact inputs. Similarly, arbitrary numerical ratings are assigned for the relationship chart. This paper presents a distinct methodology for the facility layout process using a fuzzy decision-making system for handling inexact, vague data. The selection routine for the placement of facilities (departments) in an open continual plane is developed by using a multifactor fuzzy inference system. It considers both qualitative and quantitative factors that influence the layout structure. A two-tier fuzzy inference system is proposed to compare the proposed layout methodology with that of a conventional selection routine with respect to personnel flow cost, dead space and the minimum required area of the layout. The suggested distinct methodology is coded in C⁺⁺ language and implemented in a personal computer. The experimental results for a test problem with six departments, 30 activities (moves) and four influencing factors are illustrated with encouraging results under a fuzzy multicriteria environment.     

An exact penalty function method for optimising QAP formulation in facility layout problem

A quadratic assignment problem (QAP), which is a combinatorial optimisation problem, is developed to model the problem of locating facilities with material flows between them. The aim of solving the QAP formulation for a facility layout problem (FLP) is to increase a system’s operating efficiency by reducing material handling costs, which can be measured by interdepartmental distances and flows. The QAP-formulated FLP can be viewed as a discrete optimisation problem, where the quadratic objective function is optimised with respect to discrete decision variables subject to linear equality constraints. The conventional approach for solving this discrete optimisation problem is to use the linearisation of the quadratic objective function whereby additional discrete variables and constraints are introduced. The adoption of the linearisation process can result in a significantly increased number of variables and constraints; solving the resulting problem can therefore be challenging. In this paper, a new approach is introduced to solve this discrete optimisation problem. First, the discrete optimisation problem is transformed into an equivalent nonlinear optimisation problem involving only continuous decision variables by introducing quadratic inequality constraints. The number of variables, however, remains the same as the original problem. Then, an exact penalty function method is applied to convert this transformed continuous optimisation problem into an unconstrained continuous optimisation problem. An improved backtracking search algorithm is then developed to solve the unconstrained optimisation problem. Numerical computation results demonstrate the effectiveness of the proposed new approach.     

MULTI-HOPE: A tool for multiple floor layout problems

The objective of most facility layout problems is to minimize material handling cost, which is directly proportional to both the distance between the machines and the mix, as well as the volume of products handled. The mix and volume of products are dependent on the demand patterns, and the distance is dependent on the layout plan used for the facility. Because it is relatively difficult to change the demand patterns, and hence the mix and volume of products, the primary focus of most designers has been to deal with the distance attribute of the material handling costs. The limitations of available horizontal space create a need to explore vertical expansion of facilities. This brings up new aspects of vertical material handling and flow that need to be considered in the facility design problem. In this paper, we present a genetic algorithm-based heuristic for generating block layouts for multiple-floor layout problems. This approach produces better solutions than existing simulated annealing-based heuristics for all but one of five multiplefloor test problems available in the literature.     

A Material Handling System Selection Model

A technique is presented which can be used to design, or assist in the design of, an integrated materials handling system for a manufacturing facility or a major department of the facility. The developed procedure selects the materials handling equipment to be used to perform a given set of moves in order to miriimize the system's costs associated with the handling, assuming the plant arrangement remains fixed. To demonstrate the selection procedure, an example problem is presented. Since the method is heuristic, no claim of optimality is made.     

Computer-based FMS facilities design tool

FMS layout design is a complex process, involving a large number of alternatives, which contributes generously to the usual two-year FMS planning lead time. The need for a comprehensive, yet easy-to-use methodology or tool which can reduce this large number of alternatives to a more reasonable figure has motivated this research. A survey of existing FMSs was undertaken with the intention of identifying some of the more common (dominant) types of layouts, and to develop, if possible, a methodology for the selection of such layouts. However, almost every FMS was found to have a unique layout. For a given FMS under consideration, the capabilities with respect to the parts which can be manufactured is essentially given. The determining features of the resultant design of the FMS, therefore, are primarily based upon the design of the material handling system which integrates the FMS. However, as the number of machines in a FMS increase, the number of part sequences and alternate configurations increase at a dramatic rate. To assist in the preliminary design process, an interactive computer-based program has been developed to aid the search for non-inferior layouts to suit the exact part sequence needs of each FMS. Six criteria-three related to the distances parts travel during manufacturing and three related to the capital costs of the FMS-are provided to assist the user in selecting an appropriate arrangement. The program is described and its use is demonstrated in developing improved arrangements over an example FMS which was published in the literature. Although the reader is cautioned that the results were developed using only static measures, the results do indicate that significantly improved designs are possible using the proposed methodology     

Optimal cost design of flow lines with reconfigurable machines for batch production

Modular reconfigurable machines offer the possibility to efficiently produce a family of different parts. This paper formalises a cost optimisation problem for flow lines equipped with reconfigurable machines which carry turrets, machining modules and single spindles. The proposed models take into account constraints related to: (i) design of machining modules, turrets, and machines, (ii) part locations, and (iii) precedence relations among operations. The goal is to minimise equipment cost while reaching a given output and satisfying all the constraints. A mixed integer programming model is developed for the considered optimisation problem. The approach is validated through an industrial case study and extensive numerical experiments.     

EXCITE: Expert consultant for in-plant transportation equipment

The cost of handling material is a vital factor in the facilities design process, whether it is for a new facility or for the redesign of an existing facility. Handling activities generally account for 30 to 40% of production costs, but in some industries they can be as high as 70%. Well designed handling systems are thus crucial for reduced costs and increased profits.

A key task in the material handling system design process is the selection and configuration of equipment for transport and storage in a facility. Material handling equipment selection is a complex, tedious task, and there is usually more than one good answer for any particular situation. A number of good quantitative techniques are available to aid the industrial engineer in determining layout design with the aim of reducing material handling cost. Unfortunately, there are few tools other than checklists to aid the engineer in the selection of appropriate, cost-effective material handling equipment. Analytical models are not often applied in industry because they generally consider only quantifiable factors such as cost and utilization and are difficult to implement.

This paper describes a knowledge-based approach for addressing the major factors that influence equipment selection. The research effort involved two major activities: compilation of a knowledge base from an in-depth review and modification of traditional checklists and published literature on equipment selection; and development of a prototype expert system for material handling equipment selection.     

AGV controlled FMS

One of the key factors that prevent the implementation of Flexible Manufacturing Systems (FMS) is the elaborate cost associated with the control software. In a FMS there is often a wide range of equipment, such as personal computers, Programmable Logical Controllers (PLCs), CNC Machines or robots, each of these having their own 'intelligence' and library of data. Providing a means of communication between these individual controllers has traditionally been achieved using a Local Area Network (LAN). This proves more expensive when traditional manual operated machines have to be integrated into the system. The model described in this paper provides an alternative to the conventional use of a LAN in a FMS environment. In the design solution, an Automatically Guided Vehicle (AGV) is used as both the materials handling unit and the communications line linking each station to the host controller. Communications between the AGV and peripheral equipment is achieved using a standard infrared data link, eliminating hard-wiring and network protocols. A simulation model has been developed to demonstrate the feasibility of such a system, using industrial data. The software package Witness is used to develop the simulation model. The objective from developing this simulation model is to test whether an AGV is capable of meeting the demands of such a scenario. The research undertaken aims to test this by modelling an existing factory layout. Using this layout and captured machining times and part routes, from the factory database, the feasibility of such AGV controlled production system is established. The model shows that such a system is plausible in a scenario where machine times are high and the distance between machines is large.     

A mixed-integer programming formulation for the double row layout of machines in manufacturing systems

The Double Row Layout Problem (DRLP) is the problem of allocating a given set of machines on both sides of a straight line corridor so as to minimise the total cost of transporting materials among machines. The DRLP occurs in several manufacturing plants, particularly in semiconductor manufacturing. While it has a large practical importance, the problem is very difficult to solve to optimality. In this paper, we construct a mixed-integer programming (MIP) formulation of the problem, which favourably compares to a previously published MIP formulation. The new model is found to present similar performance to another published MIP formulation, and it has the advantage of being more intuitive for handling qualitative inputs that may be required in a layout refinement phase.     

Development of a simulation-based optimisation for controlling operation allocation and material handling equipment selection in FMS

Flexible manufacturing system (FMS) is described as a set of computerised numerical controlled machines, input–output buffers interconnected by automated material handling devices. This paper develops a bi-objective operation allocation and material handling equipment selection problem in FMS with the aim of minimising the machine operation, material handling and machine setup costs and maximising the machine utilisation. The proposed model is solved by a modified chaotic ant swarm simulation based optimisation (CAS²O) while applying pre-selection and discrete recombination operators is surveyed a capable method to simulate different experiments of FMS problems. A test problem is selected from the literature to evaluate the performance of the proposed approach. The results validate the effectiveness of the proposed method to solve the FMS scheduling problem.     

A study on crate sizing problems

This paper studies the crate sizing problem to predetermine optimal standard packaging crate sizes for a demand of assorted sizes of products to minimise space and costs. The crate sizing problem is a real world logistics scenario faced by an existing multinational corporation in the applied chemistry industry. Customer demands come in a mix of rolls to be packaged in individual crates and then shipped in shipping containers from plants to customers. Firstly, a linear crate length optimisation model is introduced with the objective to minimise the total loss of extra space inside the crates for a given distribution of customer demands. In order to take inventory costs of crates into consideration, a second problem is introduced to both find the optimal number of crate types and the corresponding lengths such that the total costs of packaging and inventory are minimised. The latter problem is first formulated as a non-linear optimisation model and then solved using dynamic programming approach to balance the trade-off between the number of crate types and the penalty cost for space wastage inside the crates.     

Unequal-area,fixed-shape facility layout problems using the firefly algorithm

In manufacturing industries, the facility layout design is a very important task, as it is concerned with the overall manufacturing cost and profit of the industry. The facility layout problem (FLP) is solved by arranging the departments or facilities of known dimensions on the available floor space. The objective of this article is to implement the firefly algorithm (FA) for solving unequal-area, fixed-shape FLPs and optimizing the costs of total material handling and transportation between the facilities. The FA is a nature-inspired algorithm and can be used for combinatorial optimization problems. Benchmark problems from the previous literature are solved using the FA. To check its effectiveness, it is implemented to solve large-sized FLPs. Computational results obtained using the FA show that the algorithm is less time consuming and the total layout costs for FLPs are better than the best results achieved so far.     

Determination of economic order quantities (EOQ) in an integrated material flow system

The material flow system is the backbone of a manufacturing system as it provides both physical and operational structure. Each component (material handling, until load size, storage space, layout, etc) is a difficult problem to address on its own; however, it is imperative that components be addressed concurrently due to their interactions. This paper explores the relationships between the components in the material flow system with respect to determining the economic order quantity. This is in contrast to the traditional EOQ model, which considers only order cost, inventory cost, and demand, ignoring other material flow system issues. A multi-item economic order quantity (EOQ) model under a storage space limit is considered with respect to material handling equipment selection and requirements, unit load size, and flow path selection. The integrated material flow system problem is mathematically formulated as a large scale, nonlinear integer programming model and a heuristic solution procedure is developed. The impact of using an integrated approach to determine the EOQ is illustrated and solutions are compared to a lower bound. It is found that an integrated approach provides consistent and significant improvement in the overall solution quality.