Application of expert systems and pattern recognition methodologies to facilities layout planning

This paper deals with two basic concepts of artificial intelligence (AI), from a facilities layout problem domain perspective. In this work, the facilities layout problem is treated as a multi-objective situation. From conventional multi-objective perspective, the philosophy underlying this work is not a different one. However, the qualitative constraints are handled via a symbolic manipulation structure. The two conceptualizations are: (a) an expert system and (b) a pattern recognition system. In the expert system, the heuristics used are based on the augmented transition networks of natural language processing. In the pattern recognition system, the use of productions rules to capture the expert knowledge is illustrated. For both the systems example problems are given.     

Effective material flow at an assembly facility

Effective material flow in an assembly facility leads to reduced material handling costs and increased productivity. This research focuses on improving the flow of materials for an assembly facility that receives supplied parts through receiving docks and transfers the parts to material storage locations and then to part usage locations. The locations of the receiving docks, storage locations, and line locations are predetermined, but the assignment of parts to dock locations and storage locations and the material flow paths through the facility are decision variables. Furthermore, design decisions such as the dock strategy employed and the configuration of the storage areas lead to additional decision variables. The goal is to reduce overall material handling costs by effectively receiving, storing and transferring the material from loading docks to line locations. The contribution of this research is in applying multi-commodity network flow models that integrate many of the sub-problems that are assumed to be solved a priori in many existing models. This integrated approach was used to evaluate configuration changes for a collaborating facility. One of the scenarios analysed showed an improvement in the material handling costs of nearly 10% as compared to current practices.     

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.     

Fuzzy approach to the robust facility layout in uncertain production environments

The proposed method approaches the problem of the optimal facility layout using fuzzy theory. The optimal layout is a robust layout that minimizes the total material handling cost, when the product market demands are uncertain variables, which are defined as fuzzy numbers. Since each department has a limited production capacity, not all possible combinations, deriving from each product's market demand, are taken into account because some combination could exceed the overall department's productivity. Therefore, the optimal solution results by solving a 'constrained' fuzzy optimization problem, in which the fuzzy material handling costs corresponding to the layouts are evaluated, and a ranking method, which considers the grade of pessimism of the decision maker, is established to determine the optimal layout.     

Strukturierung von Entscheidungsprozessen bei mehrfacher Zielsetzung

Zusammenfassung In diesem Beitrag werden einige Alternativen zur Strukturierung von Entscheidungsprozessen auf der Grundlage konkreter Planungsmodelle mit mehrfacher Zielsetzung vorgestellt, die zu einer Lösung von Planungsproblemen bei mehrfacher Zielsetzung beitragen können.

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Summary This paper focusses on some alternative structures of a goal formation and decision process in order to select a compromise alternative for a multiple-criteria decision problem. It is illustrated, that resolving a multiple-criteria decision conflict on the basis of a decision model with several objective functions in the sense that the decision maker finds an acceptable compromise alternative within an acceptable span of time constitutes not only a theoretical but a practicable possibility.

     

An integrated approach to the facilities and material handling system design

The facility layout problem involves the optimal location of manufacturing facilities into a workshop. The classical approach to the layout design is carried out in two separate steps: the first step is the construction of the block layout, i.e. the location of the departments into the workshop, and the second step is the design of the material handling system. The separate optimization of these two aspects of the problem leads to solutions that can be far from the total optimum. In this paper, an integrated approach to the facilities and material handling system design is proposed. Referring to a physical model, named the bay structure , and to a unidirectional AGV system, a genetic approach is proposed to individuate the locations of the departments, the positions of the pickup/delivery stations and the direction of the flow-path. The minimization of material handling cost is adopted as optimality criterion.     

Mitigation of risk in facility layout design for single and multi-period problems

The most desirable characteristic of a facility layout is its ability to maintain its efficiency over time while coping with the uncertainty in product demand. In the traditional facility layout design method, the facility layout is governed by the flow intensity between departments, which is the product flow quantity between departments. Hence, an error in the product demand assessment can render the layout inefficient with respect to material handling costs. Most of the research integrates uncertainty in the form of probability of occurrence of different from-to charts. In an environment where the variability of each product demand is independent, the derivation of ‘probabilistic from-to chart’ based scenario cannot be used to address uncertainty of individual demands. This paper presents an FLP (facility layout problem) approach to deal with the uncertainty of each product demand in the design of a facility layout. Two procedures are presented: the first procedure is utilised to assess the risk associated with the layout, while the second procedure is used to develop the layout that minimises the risk. Results from case studies have shown that the procedure produces a reduction of risk as high as 68%.     

Practical solutions for multi-objective optimization: An application to system reliability design problems

For multiple-objective optimization problems, a common solution methodology is to determine a Pareto optimal set. Unfortunately, these sets are often large and can become difficult to comprehend and consider. Two methods are presented as practical approaches to reduce the size of the Pareto optimal set for multiple-objective system reliability design problems. The first method is a pseudo-ranking scheme that helps the decision maker select solutions that reflect his/her objective function priorities. In the second approach, we used data mining clustering techniques to group the data by using the k-means algorithm to find clusters of similar solutions. This provides the decision maker with just k general solutions to choose from. With this second method, from the clustered Pareto optimal set, we attempted to find solutions which are likely to be more relevant to the decision maker. These are solutions where a small improvement in one objective would lead to a large deterioration in at least one other objective. To demonstrate how these methods work, the well-known redundancy allocation problem was solved as a multiple objective problem by using the NSGA genetic algorithm to initially find the Pareto optimal solutions, and then, the two proposed methods are applied to prune the Pareto set.     

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.     

Propagation of uncertainty by the possibility theory in Choquet integral-based decision making: application to an E-commerce website choice support

This paper is concerned with some aspects of uncertainty evaluations in multicriteria decision making (MCDM) in the framework of e-commerce website recommendation. The emphasis is on the interest of handling uncertainty with possibility distributions in the MCDM process where evaluations coming from the users present variability. Thus, the authors consider the propagation of possibility distributions through the multicriteria aggregation made by a Choquet integral that takes into account the interactions between the decision-making criteria. To support the recommendation process, location and uncertainty indicators of possibility distributions are defined, as well as their marginal contributions to the aggregated result. The proposed approach is applied here to the problem of the choice of an e-commerce website for purchase purposes, but it can also be used for dealing with uncertainty in other complex problems.     

A Multiple criteria decision aid for personnel scheduling

The personnel scheduling problem is addressed through a multiple-criteria decision system. A four-stage process is proposed which utilizes analytic models and computer simulation to develop an aggregate shift schedule. The scheduler plays a key role in generating the personnel schedule. A queueing model converts customer (task) arrival rates into personnel requirements for each scheduling period. A goal programming model utilizes these personnel requirements to generate a shift schedule, allowing the decision maker a choice in establishing scheduling priorities. Priorities can be established for workforce levels in particular periods (from two distinct points of reference), full-time workforce levels, and part-time workforce levels. By varying priority relationships, different shift schedules result. A computer simulation model is included to evaluate the schedule generated by the goal program. The results of the simulation provide the decision maker with schedule performance information. Based upon this information, the scheduler can accept the schedule, revise the schedule, or revise certain model parameters and cycle back through the solution process. The flexibility of the scheduling model is illustrated through example priority formulations and a sample scheduling problem.     

An integrated approach to determine the block layout,AGV flow path and the location of pick-up/delivery points in single-loop systems

Layout design and material handling system design are two of the major aspects of facility planning. Although both aspects directly influence each other, the classical approach to the layout design is carried out in two separate steps: in the first step the block layout, i.e. the location of the departments in the workshop, is constructed, and in the second step, the material handling system is designed. The separate optimisation of these two aspects of the problem leads to solutions that can be far from the global optimum. In this paper, we develop an integrated algorithm to design the facilities and material handling systems. We focus on single-loop AGV systems. The proposed algorithm determines the block layout, AGV single-loop flow path and pick-up delivery stations, simultaneously. The associated from–to chart and the area of departments are the principal inputs of the algorithm. The objective is minimising total material flow distance among all departments. The results of our computational experiments show the algorithm was coded using MATLAB 7.0, and that our integrated algorithm is more efficient in terms of both the objective function value and the runtime.     

Hesitant fuzzy programming technique for multidimensional analysis of hesitant fuzzy preferences

The linear programming technique for multidimensional analysis of preferences (LINMAP) is the most representative method for handling the multiple criteria decision making (MCDM) problems with respect to the preference information over alternatives. This paper utilizes the main structure of LINMAP to develop a novel hesitant fuzzy mathematical programming technique to handle MCDM problems within the decision environment of hesitant fuzzy elements (HFEs). Considering the hesitancy of the decision maker, both the pair-wise comparison preference information over alternatives and the evaluation information of alternatives with criteria are represented by the HFEs. Based on the incomplete pair-wise preference judgments over alternatives, we propose the concepts of the hesitant fuzzy consistency and inconsistency indices. Furthermore, we construct a hesitant fuzzy mathematical programming model to derive the weights of criteria and the positive-ideal solution. In this hesitant fuzzy programming model both the objective function and partial constraints’ coefficients take the form of HFEs, and an effective approach based on the ranking method of HFEs is further developed to solve the new derived model. To address the incomplete and inconsistent preference structures of criteria weights, we introduce several deviation variables and establish the bi-objective nonlinear programming model. At length, we employ a green supplier selection problem to illustrate the feasibility and applicability of the proposed technique and conduct a comparison analysis to validate its effectiveness.     

Integrating occupational health and safety in facility layout planning,part I: methodology

An influential factor affecting the efficiency of a manufacturing facility is its layout. In a production facility, measure for efficiency can be based on the total cost of transporting the items between different departments and throughout the facility. However, other factors may influence efficiency of the manufacturing facility too. As such are: supporting the organisation's vision through improved material handling, material flow and control; effectively assigning people, equipment, space and energy; minimising capital investment; adaptability and ease of maintenance; as well as providing for employee safety and job satisfaction. By incorporating health and safety measures in the initial design of a facility layout, the organisation may avoid money and manpower loss resulting from industrial accidents. This paper proposes a facility layout planning methodology which integrates the occupational health and safety (OHS) features in the early design of a facility layout. The model considers transportation cost in the facility as well as safety concerns. By this means, the OHS issues are reflected prior to the construction of a facility.     

Optimisation of facility layout design problem with safety and environmental factors by stochastic DEA and simulation approach

This article presents an integrated computer simulation–stochastic data envelopment analysis (SDEA) approach to deal with the job shop facility layout design problem (JSFLD) with stochastic outputs and safety and environmental factors. Stochastic outputs are defined as non-crisp operational and deterministic inputs. At first, feasible layout alternatives are generated under expert decision. Then, computer simulation network is used for performance modelling of each layout design. The outputs of simulation are average time-in-system, average queue length and average machine utilisation. Finally, SDEA is used with Lingo software for finding the optimum layout alternative amongst all feasible generated alternatives with respect to stochastic, safety and environmental indicators. The integrated approach of this study was more precise and efficient than previous studies with the stated outputs. The results have been verified and validated by principal component analysis. The unique features of this study are the ability of dealing with multiple inputs (including safety) and stochastic (including environmental) outputs. It also uses mathematical programming for optimum layout alternatives. Moreover, it is a practical tool and may be applied in real cases by considering safety and environmental aspects of the manufacturing process within JSFLD problems.     

A multi-objective mixed-integer programming model for a multi-floor facility layout

We consider a multi-floor facility layout problem in which the overall length and width of the facility, the size and location of each department, the number and the location of elevators and the number of floors in the facility are all modelled as decision variables. We adapt a linear approximation scheme to represent the area of each department. We consider two objective functions in our model, namely minimising material handling and facility building costs, and propose a lexicographic ordering technique to handle multiple objectives. The numerical experiments show that the slack used in the lexicographic ordering approach has a significant impact on the optimal solution. The experiments also show that the material handling cost can be significantly reduced in a multi-floor facility compared with a single-floor facility.     

Improved common weight MCDM model for technology selection

This paper presents an improvement on earlier work on a common weight multi-criteria decision-making (MCDM) approach for technology selection by (Karsak, E.E. and Ahiska, S.S., Practical common weight multi-criteria decision-making approach with an improved discriminating power for technology selection. Int. J. Prod. Res., 2005, 43, 1537–1554.) benefiting from a bisection search algorithm. The proposed algorithm enables to calculate the values of discriminating parameter, k, which appears in the introduced efficiency measure, in a systematic and robust manner rather than requiring the decision analyst to assign an arbitrary step size value. In addition, the paper presents comments on the model proposed by (Amin, G.R., Toloo, M. and Sohrabis, B., An improved MCDM DEA model for technology selection. Int. J. Prod. Res., 2006, 44, 2681–2686.) for technology selection. Finally, the robustness of the proposed decision-making framework is illustrated via several numerical examples taken from the above-mentioned papers.     

A heuristic approach on the facility layout problem based on game theory

Facility layout problems are related to the location of all facilities in a plant. Numerous research works related to facility layout have been published. The applicability of these various existing models may be limited by the fact that they all ignore competitive reactions to one's actions. In addition to external competitors, some internal problems of system such as material handling system design affect layout designs. For considering these effects, some researchers have investigated multi-objective approaches that in most cases lead to the optimisation of a weighted sum of score functions. The poor practicability of such an approach is due to the difficulty of normalising these functions and quantifying the weights. To the extent that competitors do react to a firm's actions and also the facility layout problem considers several conflicting objectives by distinct decision makers in the firm, the existing models may be oversimplifications of reality. In this paper, we modelled such a facility layout problem with conflicting objectives under a duopoly Bertrand competition as a game and solved it with a proposed simulated annealing meta-heuristic. Results obtained from solving some numerical examples confirm the effectiveness of the proposed model for the layout design.     

An extended distance-based facility layout problem

The distance-based facility layout problem with unequal-area departments has been studied by many researchers for over 30 years. Still, current approaches require certain assumptions that limit the type of solutions obtained. In this paper, we consider manufacturing systems in which replicates of the same machine type may exist in the facility, and propose an extended distance-based facility layout problem that concurrently determines the number and shape of the departments, the assignment of machines to departments, and the allocation of part flow volume to individual machines. A non-linear mixed-integer program that accurately captures the extended facility layout and part flow allocation problem, a decomposition approach that exploits the structure of the formulation using a heuristic solution procedure, as well as computational results that evaluate the proposed approach, are presented.     

A Monte Carlo simulation based heuristic procedure for solving dynamic line layout problems for facilities using conventional material handling devices

A simple procedure is proposed to identify line layout solutions when a production facility with work centres of unequal size uses conventional material handling devices and operates under stochastic demand scenarios. The procedure uses Monte Carlo simulation (MCS) to empirically search for robust solutions defined as those that simultaneously meet minimum material handling cost performance levels across all demand scenarios. The results reported in this study suggest that ‘robust’ line layout solutions can be identified using a modest volume of random sampling. The procedure and results are demonstrated through a series of sample problems.