A combined goal programming—AHP approach to maintenance selection problem

This paper presents a ‘Lexicographic’ Goal Programming (LGP) approach to define the best strategies for the maintenance of critical centrifugal pumps in an oil refinery.For each pump failure mode, the model allows to take into account the maintenance policy burden in terms of inspection or repair and in terms of the manpower involved, linking them to efficiency-risk aspects quantified as in FMECA methodology through the use of the classic parameters occurrence (O), severity (S) and detectability (D), evaluated through an adequate application of the Analytic Hierarchy Process (AHP) technique.An extended presentation of the data and results of the case analysed is proposed in order to show the characteristics and performance of this approach.     

An integrated approach to evaluating conceptual design alternatives in a new product development environment

As many companies have demonstrated over time, a conceptual design for a new product contributes greatly to an improvement in competitiveness, because it permits a reduction of costs, an increase in quality, and, often, a shortening of the time necessary to get the product on the market. That is why the evaluation of conceptual design alternatives created in a new product development (NPD) environment has long been very vital and a critical point for the future success of companies in fast-growing markets. These alternatives can be evaluated using the analytic hierarchy process (AHP), one of the most commonly used multiple criteria decision making (MCDM) techniques. This technique is used to reduce the number of conceptual design alternatives after ranking them using the scores obtained from the process. Furthermore, another technique, simulation analysis integrated with the AHP, is also used to help decision makers (product engineers or managers) perform economic analyses of the AHP's high-score alternatives using data from the generated simulation model of a real-life manufacturing system in which the final alternative is produced. In short, the objectives of this research are: first, to use the AHP technique to evaluate conceptual design alternatives in a NPD environment; second, to use a simulation generator integrated with this technique in order to perform economic analyses for the AHP's high-score alternatives. Finally, the results of both techniques, simulation and AHP, are used in a benefit/cost (B/C) analysis to reach a final decision on the conceptual design alternatives.     

A comparison of T 2 control charts with variable sampling schemes as opposed to MEWMA chart

Variable sampling plans have been widely employed to increase the power of control charts, mainly for the univariate case. In this paper, a T 2 control chart with variable sample size and variable sampling frequency is developed. Near optimum schemes are obtained to detect faster shifts in the mean vector. A comparison with a MEWMA chart is made.     

Integrating AHP with QFD for robot selection under requirement perspective

Selection of a robot is an important task, as improper selection may adversely affect a firm's production by reducing the quality of the product, thereby reducing productivity as well as profitability. To effectively select a robot for a specified job, several factors have to be considered. The objective of this paper is to explain how, using a combined AHP/QFD model, the authors are able to determine if the deployment of robots in industry helped in performance enhancement from requirement perspective. Incorporating a simple and novel cost factor measure in the proposed integrated AHP/QFD model aids justification of the implementation of a robotic system in a manufacturing firm from an economic point of view also. The proposed integrated approach also identifies technical requirements followed by customer requirements. In this paper, an integrated model combining AHP and QFD has been delineated for the industrial robot selection problem. Seven technical requirement factors have been considered for the case study.     

A screening methodology for improved solvent selection using economic and environmental assessments

Solvents are used in many applications in chemical manufacturing. An ideal solvent exhibits superior solubility, economic, and environmental impact characteristics. There are many approaches developed for identifying the best solvents, including the use of the Hansen solubility parameters, activity coefficients, toxicity properties, flammability characteristics, and methods based on structure–activity relationships. In this paper, a general methodology is developed to perform solvent selection using solubility matching, economic evaluation and environmental assessments. We propose a five-step approach to perform this task: 1.Solubility matching by applying Hansen solubility parameters 2.Process-specific property constraints, such as boiling point and melting point 3.Economic assessment via process simulation to investigate solvent usage, energy consumption, equipment investment and other operating costs 4.Environmental impact assessment based on process simulation and emission estimation 5.Solvent ranking using economic and environmental objective functions A case study is evaluated using this methodology. This methodology provides a general and effective approach to solvent selection in the context of the entire process, balancing economic, environmental, and operational performances. Electronic Publication     

Global supplier selection: a fuzzy-AHP approach

Global supplier selection has a critical effect on the competitiveness of the entire supply chain network. Research results indicate that the supplier selection process appears to be the most significant variable in deciding the success of the supply chain. It helps in achieving high quality products at lower cost with higher customer satisfaction. Apart from the common criteria such as cost and quality, this paper also discusses some of the important decision variables which can play a critical role in case of the international sourcing. The importance of the political-economic situation, geographical location, infrastructure, financial background, performance history, risk factors, etc., have also been pointed out in particularly in the case of global supplier selection. Supplier selection problem related to the global sourcing is more complex than the general domestic sourcing and as a result it needs more critical analysis, which could not be found properly in past available literatures. This paper discusses the fuzzy based Analytic Hierarchy Process (fuzzy-AHP) to efficiently tackle both quantitative and qualitative decision factors involved in selection of global supplier in current business scenario. The fuzzy-AHP is an efficient tool to tackle the fuzziness of the data involved in deciding the preferences of the different decision variables involved in the process of global supplier selection. The triangular fuzzy numbers are used to transform the linguistic comparison of the different decision criteria, sub-criteria and performance of the alternative suppliers. The pairwise comparison matrices help in deciding the synthetic extent value of each comparison and finally, the priority weights of one alternative over another are decided in this paper. An example from a manufacturing industry searching for the global supplier for a critical component is used to demonstrate the effective implementation procedure of proposed fuzzy-AHP technique. The proposed model can provide the guidelines and directions for the decision makers to effectively select their global suppliers in the current competitive business scenario.     

Development of a component-based machining centre selection model using AHP

Machining centres are widely used in manufacturing companies all over the world. Since investments in machining centres are long-term and expensive, selection of the most appropriate machining centre is an important decision for manufacturing companies. There has been considerable effort spent in developing crisp and fuzzy multi-criteria decision-making (MCDM) models that use technical specifications provided by machining-centre manufacturers such as, axis size, power, spindle speed, tolerance, repeatability, cutting-tool change time, and number of cutting tools along with other economical and commercial factors. However, the technical specifications are directly taken from machining-centre manufacturers’ catalogues without checking their correctness, adequacies, or ability to represent the areas that are used for measurement. In such a case, one cannot be sure whether the outcomes are sound or not without a detailed check of the technical specifications, which can only be performed after actual usage of the machine itself. To overcome all such problems, an analytic hierarchy process (AHP) model that evaluates the machining centre components is developed in this paper. The new component-based AHP model is then compared with two MCDM models that use only technical specification values.     

A utility-driven approach to supplier evaluation and selection: empirical validation of an integrated solution framework

Supplier evaluation and selection (SES) problems have long been studied, leading to the development of a wide range of individual and hybrid models for solving them. However, the lack of widespread diffusion of existing SES models in the industry points to a need for simpler models that can systematically evaluate both qualitative and quantitative attributes of potential suppliers while enhancing the flexibility decision-makers need to account for relevant situational factors. Furthermore, empirical validations of existing models in SES have been few and far between. With a view to addressing these issues, this paper proposes an integrated solution framework that can be used to evaluate both tangible and intangible attributes of potential suppliers. The proposed framework combines three individual methods, namely the fuzzy analytic hierarchy process, fuzzy complex proportional assessment and fuzzy linear programming. The framework is validated through application in a Turkish textile company. The results generated using the proposed framework is compared with the actual historical data collected from the company. Additionally, a feasibility assessment is conducted on the sample supplier selection criteria employed, as well as assessment of the results generated using the proposed model.     

Fuzzy hybrid decision model for supplier evaluation and selection

This paper proposes a structured, integrated decision model for evaluating suppliers by combining the fuzzy analytical hierarchy process (FAHP) and grey relational analysis (GRA). The qualitative and partially-known information is incorporated in this decision model using the fuzzy set theory. In this proposed methodology, the weights of the evaluation criteria are calculated by using FAHP, then the ranking of the suppliers is determined by using GRA. Finally to show the robustness of the model, a sensitivity analysis is also performed. In this study, the supplier selection problem of an electroplating industry in the southern part of India was investigated, demonstrating the effectiveness of this developed integrated model. This model can help in solving the complex decision in supplier selection practice. The results generated from the model are properly validated and finally a systematic solution with decision support is provided for decision makers. This model can be integrated with other decision support systems of similar kinds of industries.     

Using AHP in determining the prior distributions on gas pipeline failures in a robust Bayesian approach

The paper proposes a robust Bayesian approach to support the replacement policy of low-pressure cast-iron pipelines used in metropolitan gas distribution networks by the assessment of their probability of failure. In this respect, after the identification of the factors leading to failure, the main problem is the historical data on failures, which is generally limited and incomplete, and often collected for other purposes. Consequently, effective evaluation of the probability of failure must be based on the integration of historical data and knowledge of company experts. The Analytic Hierarchy Process has been used as elicitation method of expert opinion to determine the a priori distribution of gas pipeline failures. A real world case study is presented in which the company expertise has been elicited by an ad hoc questionnaire and combined with the historical data by means of Bayesian inference. The robustness of the proposed methodology has also been tested.     

The analytic hierarchy process applied to maintenance strategy selection

This paper describes an application of the Analytic Hierarchy Process (AHP) for selecting the best maintenance strategy for an important Italian oil refinery (an Integrated Gasification and Combined Cycle plant). Five possible alternatives are considered: preventive, predictive, condition-based, corrective and opportunistic maintenance. The best maintenance policy must be selected for each facility of the plant (about 200 in total). The machines are clustered in three homogeneous groups after a criticality analysis based on internal procedures of the oil refinery. With AHP technique, several aspects, which characterise each of the above-mentioned maintenance strategies, are arranged in a hierarchic structure and evaluated using only a series of pairwise judgements. To improve the effectiveness of the methodology AHP is coupled with a sensitivity analysis.     

包装品数据评估系统方法的研究

在大量调查、分析和研究的基础上提出了评价包装品的指标体系，并利用数学中的层次分析法建立了包装品综合评价的数学模型，为包装品的综合评价提供了一种全面的、定量的和科学的系统方法。     

A multi-attribute selection of automated guided vehicle using the AHP/M-GRA technique

The objective of this research is to develop and implement a new methodology for multi-attribute selection of automated guided vehicle (AGV) for the material handling. The present paper proposes a modified grey relational analysis (M-GRA) method combined with analytical hierarchy approach (AHP). AHP method is used to assign the relative importance between AGV selection attributes and M-GRA method is applied to determine AGV selection utility index. A proposed AHP/M-GRA technique is more suitable for the decision-making in the presence of vagueness. The methodology is illustrated by means of an example. The study was followed by the validation and the sensitivity analysis of the AHP/M-GRA technique. The results of the study build confidence in suitability of AHP/M-GRA technique for selection of AGV alternatives.     

An integration of a hybrid modified TOPSIS with a PGP model for the supplier selection with interdependent criteria

This paper deals with the supplier selection process when the criteria of selection are not independent. The primary aim is to illustrate that ignoring the interdependencies among these criteria leads to an unrealistic decision. Since supplier selection is a multiple-criteria decision-making (MCDM) process, the general structures of the relative methods are outlined in this paper. The proposed methodology then presents a comprehensive approach to find the best ranking among the alternative suppliers of a typical product. A hybrid modified TOPSIS is integrated with a preemptive goal programming model in this study and then compared to an analytical hierarchy process (AHP) to show the effect of considering interdependencies in the supplier selection process. The results indicate that the proposed methodology provides a higher total value of purchasing (TVP) than AHP while the total cost of purchasing (TCP) of both methods are equal. Empirical proof is offered based on a case study.     

An integrated approach for machine tool selection using fuzzy analytical hierarchy process and grey relational analysis

Selecting a proper machine tool is one of the important decisions a company has to make. Companies which fail to do so face many problems which negatively affect the firm's productivity, flexibility, precision and its responsiveness capabilities. Selection of a machine tool involves a lot of criteria to be simultaneously studied and so it requires a multi-criterion decision making (MCDM) method to solve it. Also the subjectivity involved in such decisions ask for the use of theories such as fuzzy and grey which are very effective in handling subjective inputs. This paper integrates the fuzzy analytic hierarchy process (AHP) and grey relational analysis approaches for the selection of a machine tool from a given set of alternatives. Fuzzy AHP is used to calculate the priority weights of the criteria. Subsequently grey relational analysis (GRA) is employed to rank the alternatives. A well known problem existing in literature has been picked up for the numerical illustration. The results obtained in this paper are better when compared with that existing in literature.     

A hybrid risks-informed approach for the selection of supplier portfolio

In conventional supplier selection approaches, cost consideration is usually emphasised and it renders a vulnerable supply chain with various risks. This article aims to develop a quantitative approach for modelling both supply chain operational risks and disruption risks to support decision-making with regard to order allocation and risk mitigation. We introduce two types of risk evaluation models: value-at-risk (VaR) and conditional value-at-risk (CVaR). Specifically, VaR is used to measure operational risks caused by improper selection and operations of a supplier portfolio to the stochastic demand, which may frequently occur but result in relatively small losses to supply chains; CVaR is used to evaluate disruption risks that are less frequent and tend to cause significant damage. After incorporating risk factors into a probability-based multi-criteria optimisation model, different methods and parameters are compared and tested to determine the factors that may influence the supplier selection process. Computational examples by simulation are presented to illustrate the approach and how decision-makers make trade-offs between costs and hybrid risks.     

A new DEA common-weight multi-criteria decision-making approach for technology selection

This paper addresses an advanced manufacturing technology selection problem by proposing a new common-weight multi-criteria decision-making (MCDM) approach in the evaluation framework of data envelopment analysis (DEA). We improve existing technology selection models by giving a new mathematical formulation to simplify the calculation process and to ensure its use in more general situations with multiple inputs and multiple outputs. Further, an algorithm is provided to solve the proposed model based on mixed-integer linear programming and dichotomy. Compared with previous approaches for technology selection, our approach brings new contributions. First, it guarantees that only one decision-making unit (DMU) (referring to a technology) can be evaluated as efficient and selected as the best performer while maximising the minimum efficiency among all the DMUs. Second, the number of mixed-integer linear programs to solve is independent of the number of candidates. In addition, it guarantees the uniqueness of the final optimal set of common weights. Two benchmark instances are used to compare the proposed approach with existing ones. A computational experiment with randomly generated instances is further proceeded to show that the proposed approach is more suitable for situations with large datasets.     

A supplier selection model: a comparison of fuzzy logic and the analytic hierarchy process

This paper aims to compare two tools for decision makers that intend to support the decision of the selection of the appropriate supplier. Suppliers are crucial to both the efficiency and effectiveness of the performance of companies. A critical success factor of these companies is the selection of the appropriate supplier. A methodology is proposed to optimise the evaluation process based on different criteria. The proposed approach extends the one proposed by Ordoobadi (2009 Ordoobadi, SM. 2009. Development of a supplier selection model using fuzzy logic. Supply Chain Management: An International Journal, 14(4): 314–327. [Crossref], [Web of Science ®] , [Google Scholar], Development of a supplier selection model using fuzzy logic. Supply Chain Management: An International Journal, 14 (4), 314–327) who proposed the application of fuzzy logic (FL) where we use the same example case study in order to compare the analytic hierarch process (AHP) with FL. In this paper we demonstrate how we can achieve the same objective of expressing human assessments in the form of linguistic expressions by using AHP. Moreover, we demonstrate the capability to run a sensitivity analysis which helps to understand the causal relationships among the different factors. We demonstrate how this capability can help us to explain and predict the different relationships among criteria and alternatives. Moreover, we provide a measure that is able to capture the consistency of the decision maker's preferences. In our approach we provide a single unit of scale that is not only capable of ranking suppliers but also provides an understanding of the difference in scale between different suppliers which can then help to allocate resources accordingly. These facilities are not offered by Ordoobadi (2009 Ordoobadi, SM. 2009. Development of a supplier selection model using fuzzy logic. Supply Chain Management: An International Journal, 14(4): 314–327. [Crossref], [Web of Science ®] , [Google Scholar]). The proposed approach here can help companies to identify the best supplier in changing environments. The paper describes a decision model that incorporates a decision maker's subjective assessments and applies a multiple criteria decision making technique to manipulate and quantify these assessments. Unlike many similar studies, two techniques have been performed on the same case study in order to improve our understanding of the differences in the proposed techniques.     

A note on the application of the data envelopment analytic hierarchy process for supplier selection

In a very recent paper by Sevkli et al. (Sevkli, M., Koh, S.C.L., Zaim, S., Demirbag, M. and Tatoglu, E., 2007. An application of data envelopment analytic hierarchy process for supplier selection: a case study of BEKO in Turkey. International Journal of Production Research, 45 (9), 1973–2003), the data envelopment analytic hierarchy process (DEAHP) was claimed to outperform the analytic hierarchy process (AHP) method and provide a better decision for supplier selection. This note illustrates the weaknesses of the DEAHP, demonstrating the invalidity of the above claim. The case study of BEKO in Turkey is re-examined and shows that extra verification is needed to come to a decision.     

A two-way approach to supply chain partner selection

All organisations face partner selection. It is the first step in establishing partnership. Over recent decades, a one-way selection approach has been dominant in the literature. It is assumed that a buyer searches for one or more suppliers from a set of suppliers. Once the best supplier is found and selected, a partnership is formed. However, in reality, not only is the selection not a one-way process as the relationship itself is bilateral, but the existence of other buyers and suppliers also needs to be taken into account. In this study, a two-way partner selection approach is proposed, where not only the buyers evaluate suppliers, but also the suppliers have the opportunity to evaluate buyers. Considering a marketplace where there are several buyers and suppliers, an integrative model is proposed in the form of an assignment model to optimally match all the buyers and suppliers. A generalised model is also formulated to take the suppliers’ capacity and buyers’ demand into account. The proposed models are illustrated using some numerical examples. Finally, conclusions and recommendations for future research are provided.