Evaluating strategies for implementing industry 4.0: a hybrid expert oriented approach of B.W.M. and interval valued intuitionistic fuzzy T.O.D.I.M.

open access articleDeveloping and accepting industry 4.0 influences the industry structure and customer willingness. To a successful transition to industry 4.0, implementation strategies should be selected with a systematic and comprehensive view to responding to the changes flexibly. This research aims to identify and prioritise the strategies for implementing industry 4.0. For this purpose, at first, evaluation attributes of strategies and also strategies to put industry 4.0 in practice are recognised. Then, the attributes are weighted to the experts’ opinion by using the Best Worst Method (BWM). Subsequently, the strategies for implementing industry 4.0 in Fara-Sanat Company, as a case study, have been ranked based on the Interval Valued Intuitionistic Fuzzy (IVIF) of the TODIM method. The results indicated that the attributes of ‘Technology’, ‘Quality’, and ‘Operation’ have respectively the highest importance. Furthermore, the strategies for “new business models development’, ‘Improving information systems’ and ‘Human resource management’ received a higher rank. Eventually, some research and executive recommendations are provided. Having strategies for implementing industry 4.0 is a very important solution. Accordingly, multi-criteria decision-making (MCDM) methods are a useful tool for adopting and selecting appropriate strategies. In this research, a novel and hybrid combination of BWM-TODIM is presented under IVIF information

Modeling of system knowledge for efficient agile manufacturing : tool evaluation, selection and implementation scenario in SMEs

In the manufacturing world, knowledge is fundamental in order to achieve effective and efficient real time decision making. In order to make manufacturing system knowledge available to the decision maker it has to be first captured and then modelled. Therefore tools that provide a suitable means for capturing and representation of manufacturing system knowledge are required in several types of industrial sectors and types of company’s (large, SME). A literature review about best practice for capturing requirements for simulation development and system knowledge modeling has been conducted. The aim of this study was to select the best tool for manufacturing system knowledge modelling in an open-source environment. In order to select this tool, different criteria were selected, based on which several tools were analyzed and rated. An exemplary use case was then developed using the selected tool, Systems Modeling Language (SysML). Therefore, the best practice has been studied, evaluated, selected and then applied to two industrial use cases by the use of a selected opens source tool.peer-reviewe

Fit between humanitarian professionals and project requirements: hybrid group decision procedure to reduce uncertainty in decision-making

Choosing the right professional that has to meet indeterminate requirements is a critical aspect in humanitarian development and implementation projects. This paper proposes a hybrid evaluation methodology for some non-governmental organizations enabling them to select the most competent expert who can properly and adequately develop and implement humanitarian projects. This methodology accommodates various stakeholders’ perspectives in satisfying the unique requirements of humanitarian projects that are capable of handling a range of uncertain issues from both stakeholders and project requirements. The criteria weights are calculated using a two-step multi-criteria decision-making method: (1) Fuzzy Analytical Hierarchy Process for the evaluation of the decision maker weights coupled with (2) Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank the alternatives which provide the ability to take into account both quantitative and qualitative evaluations. Sensitivity analysis have been developed and discussed by means of a real case of expert selection problem for a non-profit organisation. The results show that the approach allows a decrease in the uncertainty associated with decision-making, which proves that the approach provides robust solutions in terms of sensitivity analysis

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

ODABIR MANAGERA KONTROLE KVALITETE NA OSNOVI AHP-COPRAS-G METODA: SLUČAJ U IRANU

Due to the increasing competition of globalization and fast technological improvements and world markets, demands of companies to have professional human resources are increasing too. It is an important problem of an organization to select the most appropriate personnel among the candidates. Quality control manager is important personnel in organizations and it’s so important to select the best candidate for this work. In this paper we proposed a personnel selection system based on Analytic Hierarchy Process (AHP) and Complex proportional assessment of alternatives with grey relations (COPRAS-G) method. At first seven criteria is identified including: knowledge of product and raw material properties, Experience and educational background, Administrative orientation, Behavioral flexibility, Risk evaluation ability, Payment and Team work and after that AHP applied for calculating weight of each criteria and finally using COPRAS- G method for selecting the best candidate for this job. This study can be used as a pattern for personnel selection and future researches.S obzirom na rastuću konkurentnost u globalizaciji te brzim tehnološkim napredovanjem na svjetskom tržištu, zahtjevi kompanija za profesionalnim kadrom se također povećavaju. Vrlo je važno za organizaciju biti u mogućnosti odabrati najbolji i najprimjereniji kadar među ponuđenim kandidatima. Manager kontrole kvalitete je važan kadar u bilo kojoj organizaciji tako da je iznimno važno za taj posao odabrati najbolje kandidate. U ovom radu predlažemo sustav odabira kadra zasnovan na analitičkom hijerarhijskom procesu (AHP) i kompleksnoj proporcionalnoj evaluaciji alternativa sa sivim odnosima (COPRAS-G). Isprva je identificirano sedam kriterija uključujući: znanje o proizvodu i svojstvima sirovine, iskustvo i obrazovanje, snalaženje s administracijom, fleksibilnost u ponašanju, sposobnost procjene rizika, plaćanja i timski rad te je zatim primijenjen AHP za izračunavanje težine svakog kriterija te je naposljetku korištena COPRAS-G metoda za odabir najboljih kandidata. Ova studija se može koristiti kao predložak za odabir kandidata i buduća istraživanja

Can fuzzy Multi-Criteria Decision Making improve Strategic planning by balanced scorecard?

Strategic management is momentous for organizational success and competitive advantage in an increasingly turbulent business environment. Balanced scorecard (BSC) is a framework for evaluating strategic management performance which translates strategy into action via various sets of performance measurement indicators. The main objective of this research is to develop a new fuzzy group Multi-Criteria Decision Making (MCDM) model for strategic plans selection process in the BSC. For this to happen, the current study has implemented linguistic extension of MCDM model for robust selection of strategic plans. The new linguistic reasoning for group decision making is able to aggregate subjective evaluation of the decision makers and hence create an opportunity to perform more robust strategic plans, despite of the vagueness and uncertainty of strategic plans selection process. A numerical example demonstrates possibilities for the improvement of BSC through applying the proposed model

Evaluation of e-learning web sites using fuzzy axiomatic design based approach

High quality web site has been generally recognized as a critical enabler to conduct online business. Numerous studies exist in the literature to measure the business performance in relation to web site quality. In this paper, an axiomatic design based approach for fuzzy group decision making is adopted to evaluate the quality of e-learning web sites. Another multi-criteria decision making technique, namely fuzzy TOPSIS, is applied in order to validate the outcome. The methodology proposed in this paper has the advantage of incorporating requirements and enabling reductions in the problem size, as compared to fuzzy TOPSIS. A case study focusing on Turkish e-learning websites is presented, and based on the empirical findings, managerial implications and recommendations for future research are offered