Prioritizing effective 7Ms to improve production systems performance using fuzzy AHP and fuzzy TOPSIS (case study)

This paper is aimed to present a fuzzy decision-making approach for prioritizing effective 7Ms to improve production systems performance. In this research systematic approach has been used for organization and production system inputs which named as 7Ms (Management, Manpower, Marketing, Method, Machine, Material, and Money). Linguistic values are used to assess the ratings and weights for 7Ms. These linguistic ratings can be expressed in trapezoidal or triangular fuzzy numbers. Then, a hierarchy multiple criteria decision-making (MCDM) model based on fuzzy-sets theory including FAHP and FTOPSIS are applied. The results obtained from AHP, FAHP; FTOPSIS were compared with each other. This research has been conducted on a manufacturing plant however the results can also be used for other types of organizations that are located in a competitive environment.     

Development of a decision support system for robot selection

With the availability of more different robot types and models along with their separate specifications, selecting the most appropriate robot is becoming more difficult and complicated for companies. Furthermore, a common set of robot selection criteria is not available for the decision makers. In this study, a two-phase robot selection decision support system, namely ROBSEL, is developed to help the decision makers in their robot selection decisions. In development of ROBSEL, an independent set of criteria is obtained first and arranged in the Fuzzy Analytical Hierarchy Process (FAHP) decision hierarchy. In the first elimination phase of the decision support system, the user obtains the feasible set of robots by providing limited values for the 15 requirements. ROBSEL, then, uses FAHP decision hierarchy to rank the feasible robots in the second phase. ROBSEL is illustrated and tested and several critical issues in its practical usage are explored in the paper. The applications of ROBSEL show that ROBSEL is a useful, practical and easy to use robot selection tool and improves robot selection decisions in the companies.     

Design of a decision support system for machine tool selection based on machine characteristics and performance tests

Economic globalization, together with heightened market competition and increasingly short product life cycles are motivating companies to use advanced manufacturing technologies. Use of high speed machining is increasingly widespread; however, as the technology is relatively new, it lacks a deep-rooted knowledge base which would facilitate implementation. One of the most frequent problems facing companies wishing to adopt this technology is selecting the most appropriate machine tool for the product in question and own enterprise characteristics. This paper presents a decision support system for high speed milling machine tool selection based on machine characteristics and performance tests. Profile machining tests are designed and conducted in participating machining centers. The decision support system is based on product dimension accuracy, process parameters such as feed rate and interpolation scheme used by CNC and machine characteristics such as machine accuracy and cost. Experimental data for process error and cycle operation time are obtained from profile machining tests with different geometrical feature zones that are often used in manufacturing of discrete parts or die/moulds. All those input parameters have direct impact on productivity and manufacturing cost. Artificial neural network models are utilized for decision support system with reasonable prediction capability.     

Multi‐Criteria Usability Evaluation of Electronic Devices in a Fuzzy Environment

The user‐oriented design is the most important competition issue in today's market. In recent years, user‐oriented design (i.e., usability) has become expected, particularly in electronic devices. Usability considers high user satisfaction in conjunction with user performance. Usability of electronic products is essential for high customer satisfaction as well as product life cycles in companies. Therefore, MP3 players were selected among the electronic products. Designing usable MP3 players is extremely important for users who have close interaction with them. In this study, MP3 players of different types and sizes were selected and their usability evaluated. The usability criteria used in the MP3 players' evaluation were divided into two major categories: performance and emotional expectations. The alternatives were ranked with fuzzy multi‐criteria decision‐making methods, namely, Fuzzy TOPSIS (FTOPSIS), Fuzzy Analytic Hierarchy Process (FAHP), and Fuzzy Axiomatic Design Theory (FADT), and the results were compared. Although the same decision matrices and data obtained from semantic differential experiment were used for all fuzzy multi‐criteria decision‐making methods, it is shown that different rankings were obtained. © 2012 Wiley Periodicals, Inc.     

A hybrid fuzzy MCDM approach to machine tool selection

The selection of the appropriate machine tools for a manufacturing company is one of the important points to achieving high competitiveness in the market. Besides, an appropriate choice of machine tools is very important as it helps to realize full production quickly. Today’s market offers many more choices for machine tool alternatives. There are also many factors one should consider as part of the appropriate machine tool selection process, including productivity, flexibility, compatibility, safety, cost, etc. Consequently evaluation procedures involve several objectives and it is often necessary to compromise among possibly conflicting tangible and intangible factors. For these reasons, multiple criteria decision making (MCDM) has been found to be a useful approach to solve this kind of problem. Most of the MCDM models are basically mathematical and ignore qualitative and often subjective considerations. The use of fuzzy set theory allows incorporating qualitative and partially known information into the decision model. This paper describes a fuzzy technique for order preference by similarity to ideal solution (TOPSIS) based methodology for evaluation and selection of vertical CNC machining centers for a manufacturing company in Istanbul, Turkey. The criteria weights are calculated by using the fuzzy AHP (analytical hierarchy process).     

改进GSA算法在协同制造任务分配中的应用

针对网络化协同制造中的任务分配问题,建立了以制造任务完成时间、完成成本、产品工艺质量为目标的多目标优化模型,提出了模型求解的改进遗传模拟退火（Genetic Simulated Annealing,GSA）算法。建立了协同制造任务分配的层次结构模型,应用模糊层次分析法分析了时间、成本和工艺质量等因素在协同制造任务分配过程中的相对重要性。设计了优化模型求解的改进遗传模拟退火算法,并结合具体实例验证了算法的有效性和优越性。     

A hybrid fuzzy AHP-PROMETHEE decision support system for machine tool selection in flexible manufacturing cell

The selection process of a suitable machine tool among the increased number of alternatives has been an important issue for manufacturing companies for years. This is because the improper selection of a machine tool may cause many problems that will affect the overall performance. In this paper, a decision support system (DSS) is presented to select the best alternative machine using a hybrid approach of fuzzy analytic hierarchy process (fuzzy AHP) and preference ranking organization method for enrichment evaluation (PROMETHEE). A MATLAB- based fuzzy AHP is used to determine the weights of the criteria and it is called program for Priority Weights of the Evaluation Criteria (PWEC), and the PROMETHEE method is applied for the final ranking. The proposed model is structured to select the most suitable computer numerical controlled (CNC) turning centre machine for a flexible manufacturing cell (FMC) among the alternatives which are assigned from a database (DB) created for this purpose. A numerical example is presented to show the applicability of the model. It is concluded that the proposed model has the capability of dealing with a wide range of desired criteria and to select any type of machine tool required for building an FMC.     

Development of a fuzzy decision support framework for complex multi‐attribute decision problems: A case study for the selection of skilful basketball players

The selection of skilful players is a complicated process due to the problem criteria consisting of both qualitative and quantitative attributes as well as vague linguistic terms. This study seeks to develop a decision support framework for the selection of candidates eligible to become basketball players through the use of a fuzzy multi‐attribute decision making (MADM) algorithm. The proposed model is based on fuzzy analytic hierarchy process (FAHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The model was employed in the Youth and Sports Center of Mugla, Turkey, with the participation of seven junior basketball players aged between 7 and 14. In the present study, physical fitness measurement values and observation values of technical skills were utilized. FAHP was used to determine the weights of the criteria and the observation values of technical skills by decision makers. Physical fitness measurement values were converted to fuzzy values by using a fuzzy set approach. Subsequently, the overall ranking of the candidate players was determined by the TOPSIS method. Results were compared with human experts’ opinions. It is observed that the developed model is more reliable to be used in decision making. The model architecture and experimental results along with illustrative examples are further demonstrated in the study.     

Machining process sequencing with fuzzy expert system and genetic algorithms

Traditional process planning systems are usually established in a deterministic framework that can only deal with precise information. However, in a practical manufacturing environment, decision making frequently involves uncertain and imprecise information. This paper describes a fuzzy approach for solving the process selection and sequencing problem under uncertainty. The proposed approach comprises a two-stage process for machining process selection and sequencing. The two stages are called intra-feature planning and inter-feature planning, respectively. According to the feature precedence relationship of a machined part, the intra-feature planning module generates a local optimal operation sequence for each feature element. This is based on a fuzzy expert system incorporated with genetic algorithms for machining cost optimization according to the cost-tolerance relationship. Manufacturing resources such as machines, tools, and fixtures are allocated to each selected operation to form an Operation-Machine-Tool (OMT) unit in the manufacturing resources allocation module. Finally, inter-feature planning generates a global OMT sequence. A genetic algorithm with fuzzy numbers and fuzzy arithmetic is developed to solve this global sequencing problem.     

模糊层次分析法在防空导弹武器系统效能分析中的应用

层次分析法由于能综合考虑系统各因素,因此在武器系统效能评定中有着重要的意义.但是传统的层次分析法要进行一致性的检验,计算量相对较大.简要地介绍了模糊层次分析法,并将其应用到防空导弹武器系统的效能评估中,由于模糊层次分析法可以不必进行一致性的检验,这样减小了计算量,而且通过实例分析了该方法的可行性.     

Application of fuzzy multi-criteria decision making methods for financial performance evaluation of Turkish manufacturing industries

For manufacturing industries, financial performance evaluation is very important in a highly competitive environment. Therefore, an accurate and appropriate performance evaluation is critical. As financial performance indicators reflect the competitiveness of a company, they must be carefully identified in the evaluation process. Generally, traditional accounting-based financial performance (AFP) measures are used for performance evaluation. However, these measures are not sufficient for performance evaluation solely in the modern industry time. So, value-based financial performance (VFP) measures have recently been introduced to express the company value. In this paper, we propose a new financial performance evaluation approach to rank the companies of each sector in the Turkish manufacturing industry. For this purpose, a hierarchical financial performance evaluation model is structured based on the AFP and VFP main-criteria and their sub-criteria. We use fuzzy analytic hierarchy process (FAHP) to determine the weights of the criteria. The companies are ranked according to their own manufacturing sector by using TOPSIS and VIKOR comparatively. The results show that the obtained ranks of the companies by these methods are almost same with respect to their own sectors.     

A fuzzy AHP approach to personnel selection problem

Due to the increasing competition of globalization and fast technological improvements, world markets demand companies to have quality and professional human resources. This can only be achieved by employing potentially adequate personnel. In this paper, we proposed a personnel selection system based on Fuzzy Analytic Hierarchy Process (FAHP). The FAHP is applied to evaluate the best adequate personnel dealing with the rating of both qualitative and quantitative criteria. The result obtained by FAHP is compared with results produced by Yager's weighted goals method. In addition to above-mentioned methods, a practical computer-based decision support system is introduced to provide more information and help manager make better decisions under fuzzy circumstances.     

DSS for 3PL provider selection in global supply chain: combining the multi-objective optimization model with experts’ opinions

To provide selections of logistics outsourcing providers in a global supply chain, this paper proposes a decision support system (DSS), based on fuzzy analytic network process (FANP) and preemptive fuzzy integer goal programming (PFIGP). For decision-makers, a suitable method for selecting third-party logistics (3PL) is critical under the trends of globalization and specialization. The proposed DSS for 3PL provider selection takes into consideration flexible resource and interactions among providers. When applying multiple attribute decision-making (MADM) to selection of 3PL providers, it is difficult for decision-makers to determine the feasible solution domain under limited resources, especially if the decision problems are NP-complete. Moreover, traditional mathematical programming does not incorporate experts’ evaluation of providers. This paper employs FANP to obtain experts’ scores of the providers, and then integrates the scores into PFIGP to facilitate selection of a 3PL provider with flexible resources. Finally, this paper uses genetic algorithms to solve the PFIGP. An illustrative example is also given to demonstrate such DSS. The test result shows that the degree of providers’ interaction affects the final weight of FANP.     

Fuzzy-based sustainability evaluation method for manufacturing SMEs using balanced scorecard framework

Sustainability has become a necessity, partly due to the threats created by traditional manufacturing practices, and due to regulations imposed by stakeholders. Performance evaluation is an important component of sustainability initiatives in manufacturing organizations. This study proposes a sustainability evaluation method for manufacturing SMEs using integrated fuzzy analytical hierarchal process (FAHP) and fuzzy inference system (FIS) approach. The performance indicators are identified from literature considering the characteristics of SMEs. Balanced scorecard framework is used to categorize the indicators among its four aspects. The linguistic variables are used to collect the opinions of decision makers about the performance ratings and importance of the aspects and corresponding indicators. The FAHP method is applied to determine the relative weights of measures and indicators. The performance ratings of the organization with respect to indicators and relative weights of indicators are combined to obtain the weighted performance ratings. The weighted performance ratings are considered as inputs to FIS. The hierarchal FIS is applied to derive the overall sustainability performance. Using a case study of manufacturing SME, the sustainability score of the organization was elicited in accordance with this procedure. Consequently, a sensitivity analysis of the proposed method reveals the most important basic indicators affecting overall sustainability, identifying areas which decision makers should place special attention. This method can also assist managers of larger enterprises to assess the effectiveness of their sustainability strategies, especially when dealing with suppliers from the SMEs.     

An integrated intelligent process planning system (IIPPS) for machining

A key component of computer integrated manufacturing (CIM) is computer aided process planning (CAPP). Process planning in machining involves the determination of the cutting operations and sequences, the selection of machine tools and cutting tools, the calculation of machining parameters, and the generation of CNC part programs. Industrial structures in Norway are defined as small and medium-sized companies. The important fact is how well these companies use high technologies and resources in order to improve their production efficiency, product quality, and company competition in international markets. The concept of an integrated intelligent system (IIS) is created for this purpose. A prototype system, the integrated intelligent process planning system (IIPPS), is described for machining; it was developed on the basis of an IIS and constructed using three levels of effort: (1) AutoCAD, (2) dBASE III and (3) KnowledgePro. The system may be utilized not only by a process plann ing engineer in a company, but also by students of mechanical or industrial engineering.     

A fuzzy decision support system for digital camera selection based on user preferences

Mobile phones have been the most rapidly spreading development in the field of communication and information technologies over the past decades. Nowadays, digital cameras have taken their place. The wide product range in the market, each with numerous heterogeneous technical attributes, complicates the selection of the most convenient camera for end-users. The aim of this work is to provide end-users with a decision support framework for selecting the best digital camera according to their preferences. End-users and photography experts use subjective assessments when determining their requirements and making their evaluations. The proposed decision support tool is built on the basis of fuzzy set theory. The imprecision of the subjective assessments are transformed to fuzzy triangular numbers. The fuzzy analytic hierarchy process (FAHP) and fuzzy compromise programming methodologies are applied in order to determine the relative weights of sub-criteria and criteria and to rank the digital camera alternatives, respectively.     

Technical investment planning of flexible manufacturing systems—The application of practice-oriented methods

Flexible manufacturing systems (FMS) exhibit a high degree of automation of the machining system and of the workpiece, and for the information flow systems. Therefore, these systems are amongst the most complex production installations and their technical investment planning must be undertaken with great care.This paper introduces a strategic planning procedure and describes auxiliary aids for the selection of the components and for structuring of the overall system. Computer programs for the selection of machine tools and for the simulation of the manufacturing process sequence are part of this procedure. The application of the methods is illustrated by means of several problem situations arising from industrial production companies; the examples show the practical usefulness of the developed auxiliary techniques. The planning accuracy possible by these methods reduces the investment risk associated with the use of these complex manufacturing systems.Also described is an integrated system for the technical investment planning of flexible manufacturing systems which comprises both existing methods and new auxiliary means for planning the machining systems and the technical/organizational overall concept.     

Application of fuzzy analytic network process for supplier selection in a manufacturing organisation

The contemporary manufacturing organisations are forced to adopt advanced manufacturing paradigms for sustaining in the global markets. Supply chain management is an essential ingredient of advanced manufacturing systems since outsourcing gains vital importance. Supplier selection is a vital issue concerned in the process of managing global supply chains. A conceptual model for supplier selection encompassing various criteria and sub-criteria has been developed. In this article, fuzzy analytic network process (fuzzy ANP) approach has been used for the supplier selection process. The case study has been carried out in an Indian electronics switches manufacturing company. Based on supplier selection weighted index, the best supplier has been determined. This is followed by the conduct of sensitivity analysis as well as questionnaire-based validation. The results of the validation study indicated that the application of fuzzy ANP is practically feasible and adaptable in the contemporary industrial scenario.     

Hierarchical optimal force-position control of complex manufacturing processes

A hierarchical optimal controller is developed in this paper to regulate the machining force and axis positions, simultaneously, in a micro end milling process. The process is divided into two levels of decision making. The bottom level includes the measurable states, which in this work comprises the axis positions. The top level includes the higher order objectives, which can be derived from the bottom level objectives by an aggregation relationship. In this work, the top level's objective is to regulate the machining force. A series of simulations were conducted in which the weighting between the top and the bottom level objectives is adjusted within the feasible range. The results demonstrated that excellent tracking of both axis positions and machining force are achieved during the steady state regardless of the weighting. However, the transient performance of the system could be systematically shaped to achieve better performance of either objective. For the purpose of comparison a decentralized optimal controller was constructed and simulated for the feasible range of controller weights. When the axis position errors were weighted heavily, both controllers were able to regulate the axis errors well, while the hierarchical controller had smaller machining force errors. When the machining force errors were weighted heavily, although the machining force error decreased for the decentralized controller the axis position errors increased significantly. However, with heavy machining force weighting, the hierarchical controller was able to manipulate the axial errors in a way that while the machining force error was reduced, the contour error (i.e., smallest deviation from the tool tip to the desired contour) remained small.