ADVISOR: A computer-aided material handling equipment selection system

This paper develops and describes a systematic computer-assisted methodology for the selection of material handling equipment (MHE). A microcomputer based system called ADVISOR models the material handling equipment selection process and employs information on 77 of the most common equipment types used in material transport, positioning, unit formation, and storage. The system identifies the appropriate equipment type for an application in two stages. At the primary stage, potential equipment types are identified through the use of physical requirements of the material handling activities specified by users. Eligible equipment are ranked according to their normalized accumulated rating and placed in a candidate equipment list. After this, a second stage involving an economic analysis for each eligible equipment is performed. The evaluation criteria provided by ADVISOR include present worth (PW).equivalent uniform annual cost (EUAC), return on investment (ROI), and payback period(PP) methods. Through ADVISOR, the expert-like MHE selection system recommends a ranked set of equipment based on user input data. An example problem is given in the paper to demonstrate the use of the system.     

Materials selection using complex proportional assessment and evaluation of mixed data methods

Material selection is a very fast growing multi-criteria decision-making (MCDM) problem involving a large number of factors influencing the selection process. Proper choice of material is a critical issue for the success and competitiveness of the manufacturing organizations in the global market. Selection of the most appropriate material for a particular engineering application is a time consuming and expensive process where several candidate materials available in the market are taken into consideration as the tentative alternatives. Although a large number of mathematical approaches is now available to evaluate, select and rank the alternative materials for a given engineering application, this paper explores the applicability and capability of two almost new MCDM methods, i.e. complex proportional assessment (COPRAS) and evaluation of mixed data (EVAMIX) methods for materials selection. These two methods are used to rank the alternative materials, for which several requirements are considered simultaneously. Two illustrative examples are cited which prove that these two MCDM methods can be effectively applied to solve the real time material selection problems. In each example, a list of all the possible choices from the best to the worst suitable materials is obtained which almost match with the rankings as derived by the past researchers.     

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.     

Cutting tool material selection using grey complex proportional assessment method

In today’s metalworking industry, many types of materials, ranging from high carbon steel to ceramics and diamonds, are used as cutting tools. Because of the wide range of conditions and requirements, no single cutting tool material meets all the needs of machining applications. Each tool material has its own properties and characteristics that make it best for a specific machining application. While evaluating a cutting tool material for a machining operation, the applicability is dependant on having the correct combination of its physical properties. Thus, it is extensively important to select the most appropriate cutting tool material with the desired properties for enhanced machining performance. This paper considers an exhaustive list of 19 cutting tool materials whose performance are evaluated based on ten selection criteria. The grey complex proportional assessment (COPRAS-G) method is then applied to solve this cutting tool material selection problem considering grey data in the decision matrix. Synthetic single crystal and polycrystal diamonds emerge out as the best two choices. Oil quenched tool steel (AISI O2) and powder metal tool steel (AISI A11) may also be used as the suitable cutting tool materials. Sialon and sintered reaction bonded silicon nitride are the worst chosen cutting tool materials.     

Selection of materials using compromise ranking and outranking methods

Selection of proper materials for different components is one of the most challenging tasks in the design and development of products for diverse engineering applications. Materials play a crucial and important role during the entire design and manufacturing process. Wrong selection of material often leads to huge cost involvement and ultimately drives towards premature component or product failure. So the designers need to identify and select proper materials with specific functionalities in order to obtain the desired output with minimum cost involvement and specific applicability. This paper attempts to solve the materials selection problem using two most potential multi-criteria decision-making (MCDM) approaches and compares their relative performance for a given material selection application. The first MCDM approach is ‘Vlse Kriterijumska Optimizacija Kompromisno Resenje’ (VIKOR), a compromise ranking method and the other one is ‘ELimination and Et Choice Translating REality’ (ELECTRE), an outranking method. These two methods are used to rank the alternative materials, for which several requirements are considered simultaneously. Two examples are cited in order to demonstrate and validate the effectiveness and flexibility of these two MCDM approaches. In each example, a list of all the possible choices from the best to the worst suitable materials is obtained taking into account different material selection criteria. The rankings of the selected materials almost corroborate with those as obtained by the past researchers.     

A subjective and objective integrated multiple attribute decision making method for material selection

The selection of an optimal material for an engineering design from among two or more alternative materials on the basis of two or more attributes is a multiple attribute decision making (MADM) problem. The selection decisions are complex, as material selection is more challenging today. There is a need for simple, systematic, and logical methods or mathematical tools to guide decision makers in considering a number of selection attributes and their interrelations and in making right decisions. This paper proposes a novel MADM method for material selection for a considered design problem. The method considers the objective weights of importance of the attributes as well as the subjective preferences of the decision maker to decide the integrated weights of importance of the attributes. Furthermore, the method uses fuzzy logic to convert the qualitative attributes into the quantitative attributes. Three examples are presented to illustrate the potential of the proposed method.     

A weighted approach for assembly line design with station paralleling and equipment selection

This paper studies the problem of assembly line design, focusing on station paralleling and equipment selection. Two problem formulations, minimizing the number of stations, and minimizing the total cost, are discussed. The latter formulation is demonstrated by several examples, for different assembly system conditions: labor intensive or equipment intensive, and with task times that may exceed the required cycle time. It is shown that the problem of assembly system design with parallel stations can be treated as a special case of the problem of equipment selection for an assembly line. A branch and bound optimal algorithm developed for the equipment selection problem is adapted to solve the parallel station problem. Experiments are designed to investigate and demonstrate the influence of system parameters, such as assembly sequence flexibility and cycle time, on the balancing improvement due to station paralleling. An ILP formulation is developed for the combined problem of station paralleling with equipment selection, and an optimal solution of an example problem is presented.     

A quality function deployment-based model for materials selection

Materials play a key role during the entire product design and manufacturing phase as a wrongly selected material may often lead to premature product failure causing loss of revenue and repute of the concerned manufacturing organization. While selecting the most suitable material for a specific application, the designers often need a sound and systematic methodology to deal with this problem having multiple candidate alternative choices and conflicting objectives. Most of the previously applied methodologies for material selection have either adopted criteria weights estimated using subjective judgments of the designers or failed to give due emphasis on the voice of the customers to meet their requirements. In this paper, a maiden venture is taken to solve the material selection problems using a quality function deployment (QFD)-based approach that can integrate the voice of the customers for a product with its technical requirements. The applicability and solution accuracy of this QFD-based material selection model is demonstrated with the help of four illustrative examples. To ease out the materials selection decision-making process, a user-friendly software prototype in Visual BASIC 6.0 is also developed.     

Application of fuzzy VIKOR and environmental impact analysis for material selection of an automotive component

Material selection is a complex process, since the process includes many criteria, determination of criteria weight and the most important factor is that the selection of appropriate criterion. The last factor indicates that the criterion must be selected in a manner, such that the selection based upon the known material parameters and the requirements of the application. Therefore the material selection can be done using MCDM (Multi Criterion Decision Making) methods. Since the inputs provided by the decision maker in linguistic manner, there is a possible chance of getting incomplete problems. So in order to overcome the problem, the inputs could be provided as fuzzy numbers. Since fuzzy set represents the uncertainty in human perceptions. In this paper, VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian, means Multicriteria Optimisation and Compromise Solution) has been used a MCDM tool for the selection of alternate material for instrument panel used in electric car and in order to evaluate this selection process in fuzzy environment, fuzzy based VIKOR is used. In addition to the fuzzy VIKOR method, the environmental impacts are also considered and compared for the four materials. The results achieved in both the assessment, showed that Polypropylene could be an alternate material for the instrument panel. The objective of this study is to develop a rational method to select the best material for an application based upon known material parameters and the requirements of the application.     

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.     

Pre-selection of suppliers through an integrated fuzzy analytic hierarchy process and max-min methodology

There are a variety of analytical models for supplier selection ranging from simple weighted techniques to complex mathematical programming approaches. However, these models are specifically aimed at supporting a decision maker in a single phase, especially in the final selection phase and they have failed to consider the supplier selection process from a holistic point of view. Although the methodology presented in this paper primarily focused on the prequalification of potential suppliers, the outputs of the previous phases, namely problem definition and formulation of criteria, are used as inputs in this methodology. The methodology utilises a fuzzy analytic hierarchy process (AHP) method to determine the weights of the pre-selected decision criteria, a max-min approach to maximise and minimise the supplier performances against these weighted criteria, and a non-parametric statistical test to identify an effective supplier set. This information supports decision makers in making the final selection with effective alternative choices. Potential application of the proposed methodology is demonstrated in Audio Electronics in Turkey's electronics industry.     

Optimal 3D layout of industrial facilities

Facilities layout is concerned with the spatial arrangement of a set of departments or equipment items. This is an important stage at the design level, which often results in a complex problem due to the high number of decisions involved. A Mixed Integer Linear Programming (MILP) formulation, for the optimal layout of facilities within a two-dimensional (2D) continuous space has been developed (Barbosa-Póvoa et al . 2001). In this paper, the proposed model is extended to account for the location of equipment units within a 3D multi-floor continuous space. Different topological characteristics are considered such as equipment items orientation, distance restrictions, equipment connectivity inputs and outputs, rectangular and irregular equipment shapes, space availability and multifloor locations. In operational terms, production or operational sections are modelled as well as safety and operability restrictions. The final model is again described as a MILP where binary variables characterize topological choices and continuous variables describe the distances and locations involved. Finally, the applicability of the proposed formulation is shown through the resolution of a set of representative examples exploring the different model characteristics.     

An integrated methodology for automating the determination of layout and materials handling system

There is a severe scanty of models and solution techniques for the determination of layout and the materials handling system when neither are fixed. This is a complex problem for which this paper proposes a new integrated methodology using a knowledge-based/optimisation approach to the problem. The knowledge-base consists of facts and rules to determine the feasibility of using a materials handling equipment type for a given move. The optimisation part determines the layout of machines minimising the materials handling costs and the dead space in the layout using a multi-criteria optimisation model. The methodology aims to minimise materials handling costs, aisle space usage and dead-space in the resulting layout. It is particularly applicable to heavy manufacturing environments. The system outputs the optimum location, configuration and orientation of machines, and the material handling equipment types, their design capacities, utilisations and the assignment of moves to each item of materials handling equipment. The results of a successful application to an example problem are given.     

A novel hybrid multiple criteria decision making model for material selection with target-based criteria

In engineering design, the decision to select an optimal material for a particular product is a problem requiring multi-criteria decision analysis that involves both qualitative and quantitative factors. The evaluation of alternative materials may be based on imprecise information or uncertain data. Furthermore, there can be significant dependence and feedbacks between the different criteria for material selection. However, most existing decision approaches cannot capture these complex interrelationships. In response, this paper proposes a general framework for evaluating and selecting the best material for a given application. A novel hybrid multiple criteria decision making (MCDM) model combining DEMATEL-based ANP (DANP) and modified VIKOR is used to solve the material selection problems of multiple dimensions and criteria that are interdependent. Moreover, target-based criteria as well as cost and benefit criteria can be addressed simultaneously in the proposed model. Finally, an empirical case concerning the bush material selection for a split journal bearing is presented to illustrate the potential of the new model. The results show that the proposed method for material selection is effective and provides meaningful implications for designers and engineers to refer.     

An Algorithm for the Manufacturing Equipment Selection Problem

This paper provides a unified framework in which product and process demands can be related to manufacturing system requirements. A nonlinear cost minimization model is developed that can be used by facility planners to guide the analyses underlying the equipment selection problem. The approach extends current work by accounting for machine flexibility. The objective is to determine how many of each machine type to purchase, as well as what fraction of the time each piece of equipment will be configured for a particular type of operation.

The resultant problem is solved with a depth-first branch and bound routine that employs a greedy set covering heuristic to find good feasible solutions. This permits early fathoming and greatly contributes to the efficiency of the algorithm. A small example is presented to highlight the computations. This is followed by a discussion of me results for a series of test problems designed to evaluate overall algorithmic performance. We show mat 16 process, 25 machine problems can be readily solved in less than 6 minutes on a microcomputer.     

Inverse Analysis of Impact Test Data: Experimental Study on Polymeric Materials Displaying Brittle Behaviour

This paper deals with the influence of the testing equipment on impact load measurements. A previously developed method of analysis and processing of the experimental data based on a refined analogical model of the impact event and inverse problem techniques is used. This method makes it possible to obtain the mechanical response of the material, notwithstanding the disturbance of the dynamic effects associated to the test. Results from tests carried out both on falling weight and swing pendulum instrumented testing machines are compared. It is shown that this method can give an accurate estimation of the actual bending force in impact testing independent of the testing equipment.     

A knowledge-based system for materials selection in mechanical engineering design

This paper studies various work on the development of computerized material selection system. The importance of knowledge-based system (KBS) in the context of concurrent engineering is explained. The study of KBS in material selection in an engineering design process is described. The development in materials databases, which sometimes serve as material selection packages, is also discussed. The use of KBS in material selection and the application in the domain of polymeric-based composite are chosen as typical examples.     

A material selection approach to evaluate material substitution for minimizing the life cycle environmental impact of vehicles

Weight reduction is commonly adopted in vehicle design as a means for energy and emissions savings. However, selection of lightweight materials is often focused on performance characteristics, which may lead to sub optimizations of life cycle environmental impact. Therefore systematic material selection processes are needed that integrate weight optimization and environmental life cycle assessment. This paper presents such an approach and its application to design of an automotive component. Materials from the metal, hybrid and polymer families were assessed, along with a novel self-reinforced composite material that is a potential lightweight alternative to non-recyclable composites. It was shown that materials offering the highest weight saving potential offer limited life cycle environmental benefit due to energy demanding manufacturing. Selection of the preferable alternative is not a straightforward process since results may be sensitive to critical but uncertain aspects of the life cycle. Such aspects need to be evaluated to determine the actual benefits of lightweight design and to base material selection on more informed choices.     

An integrated material flow system approach for determining the economic production quantity (EPQ)

Traditionally, the analysis of material flow systems has focused on each of the individual components of the system separately (i.e. material handling, production lot size, unit load size, flow path, layout, space, etc). Even though each component is difficult to address on its own, it is imperative that they 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 production quantity (EPQ). This is in contrast to the traditional EPQ model, which considers only set-up cost, inventory cost, and demand, while ignoring other material flow system issues. A multi-item economic production quantity 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 EPQ is illustrated and solutions are compared to both a lower bound and a traditional sequential approach. It is found that an integrated approach provides consistent and significant improvement in the overall solution quality.     

Book review of Global Strategic Management,by P. Lasserre,Palgrave Macmillan,Basingstoke, 2003, xx + 454 pp., £24.99, softcover (ISBN 0 333 79375 7)

This paper considers the simultaneous scheduling of material handling transporters (such as automatic guided vehicles or AGVs) and manufacturing equipment (such as machines and workcentres) in the production of complex asembled product. Given the shipping schedule for the end-items, the objective of the integrated problem is to minimize the cumulative lead time of the overall production schedule (i.e. total makespan) for on-time shipment, and to reduce material handling and inventory holding costs on the shop-floor. The problem of makespan minimization is formulated as a transportation integrated scheduling problem, which is NP-hard. For industrial size problems, an effective heuritsic is developed to simultaneouly schedule manufacturing and material handling operations by exploting the critical path of an integrated operation network. The performance of the proposed heuristic is evaluated via extensive numerical studies and compared with the traditional sequential scheduling approach. The superiority of the integrated heuristic is well documented.