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

An Integration of Rank Order Centroid, Modified Analytical Hierarchy Process and 0-1 Integer Programming in Solving A Facility Location Problem

Hadhramout province is the major producer of dates in The Republic of Yemen. Despite producing substantial quantity and quality of dates, the business losses are still high. The situation worsens with the widespread of the black market activities. Recently, the Yemeni government has issued an agreement stating the importance of building a date palm packaging factory as a resolution to the problems. Hence, this study aims to identify the best location for a date palm packaging factory among the seven districts which produce most of the date palm supplies in Hadhramout. The selection was based on eleven criteria identified by several representatives from the farmers and the local councils. These criteria were market growth, proximity to the markets, proximity to the raw materials, labor, labor climate, suppliers, community, transportation cost, environmental factors, production cost, and factory set up cost. The level of importance and the respective weight of each criterion were calculated using two different approaches, namely, Analytic Hierarchy Process (AHP) and Rank Order Centroid (ROC). In applying AHP, a slight modification was made in the pairwise comparison exercises that eliminated the inconsistency problem faced by the standard AHP pairwise comparison procedure. Likewise, in applying ROC, a normalization technique was proposed to tackle the problem of assigning weights to criteria having the same priority level, which was neither clarified nor available in the standard ROC. Both proposed techniques revealed that suppliers were the most important criterion, while community was regarded to be the least important criterion in deciding the final location for the date palm factory. Combining the criteria weights together with several hard and soft constraints that were required to be satisfied by the location, the final location was determined using three different mathematical models, namely, the ROC combined with 0-1 integer programming model, the AHP combined with 0-1 integer programming model, and the mean of ROC and AHP combined with 0-1 integer programming model. The three models produced the same result; Doean was the best location. The result of this study, if implemented, would hopefully help the Yemeni government in their effort to improve the production as well as the management of the date palm tree in Hadhramout

The state of the art development of AHP (1979-2017): A literature review with a social network analysis

Although many papers describe the evolution of the analytic hierarchy process (AHP), most adopt a subjective approach. This paper examines the pattern of development of the AHP research field using social network analysis and scientometrics, and identifies its intellectual structure. The objectives are: (i) to trace the pattern of development of AHP research; (ii) to identify the patterns of collaboration among authors; (iii) to identify the most important papers underpinning the development of AHP; and (iv) to discover recent areas of interest. We analyse two types of networks: social networks, that is, co-authorship networks, and cognitive mapping or the network of disciplines affected by AHP. Our analyses are based on 8441 papers published between 1979 and 2017, retrieved from the ISI Web of Science database. To provide a longitudinal perspective on the pattern of evolution of AHP, we analyse these two types of networks during the three periods 1979?1990, 1991?2001 and 2002?2017. We provide some basic statistics on AHP journals and researchers, review the main topics and applications of integrated AHPs and provide direction for future research by highlighting some open questions

The state of the art development of AHP (1979-2017): a literature review with a social network analysis

Although many papers describe the evolution of the analytic hierarchy process (AHP), most adopt a subjective approach. This paper examines the pattern of development of the AHP research field using social network analysis and scientometrics, and identifies its intellectual structure. The objectives are: (i) to trace the pattern of development of AHP research; (ii) to identify the patterns of collaboration among authors; (iii) to identify the most important papers underpinning the development of AHP; and (iv) to discover recent areas of interest. We analyse two types of networks: social networks, that is, co-authorship networks, and cognitive mapping or the network of disciplines affected by AHP. Our analyses are based on 8441 papers published between 1979 and 2017, retrieved from the ISI Web of Science database. To provide a longitudinal perspective on the pattern of evolution of AHP, we analyse these two types of networks during the three periods 1979–1990, 1991–2001 and 2002–2017. We provide some basic statistics on AHP journals and researchers, review the main topics and applications of integrated AHPs and provide direction for future research by highlighting some open questions

Design and Optimization of Closed-Loop Supply Chain Management

Because of cost and environmental concerns, reverse supply chain (RSC) has received a lot of attention. RSC is defined as the activities of the collection and recovery of product returns in supply chain management. The integration of forward supply chain (FSC) and RSC results in a closed-loop supply chain (CLSC). In this dissertation, FSC, RSC, and CLSC are introduced. Then, the research objectives are mentioned. The objective of this dissertation is to develop effective approaches to support closed-loop supply chain configurations and analyses, especially develop methodologies to examine impacts of multi-objectives, and uncertainty on CLSC. In Chapter 2, literature of CLSC configuration is reviewed including deterministic and uncertain models. In addition, gaps in the literature are mentioned. In Chapter 3, a facility location model is examined. After problem definition, a mixed-integer linear programming model is proposed. Then, the model is developed to consider multi-objectives under uncertain demand and return. In Chapter 4, a CLSC network is examined. In this chapter, an integrated model for CLSC configuration and supplier selection is proposed and a solution approach is developed for the multi-objective model. A numerical example is used to validate the model. In Chapter 5, a three stage model for closed-loop supply chain configuration is proposed based on a general network. It is supposed that demand is an uncertain parameter. Besides, an illustrative example is applied to show the three-stage model. In addition, managerial insights are discussed in this chapter. In Chapter 6, a mixed-integer linear programming model is proposed to configure a CLSC network. The network has been designed based on product life cycle. The objective is to maximize profit by determining quantity of parts and products in the network. We also extend the model for the condition that the remanufactured products are sent to the secondary market. Finally in Chapter 7, conclusions and future works are provided

Robust Multi-Objective Sustainable Reverse Supply Chain Planning: An Application in the Steel Industry

In the design of the supply chain, the use of the returned products and their recycling in the production and consumption network is called reverse logistics. The proposed model aims to optimize the flow of materials in the supply chain network (SCN), and determine the amount and location of facilities and the planning of transportation in conditions of demand uncertainty. Thus, maximizing the total profit of operation, minimizing adverse environmental effects, and maximizing customer and supplier service levels have been considered as the main objectives. Accordingly, finding symmetry (balance) among the profit of operation, the environmental effects and customer and supplier service levels is considered in this research. To deal with the uncertainty of the model, scenario-based robust planning is employed alongside a meta-heuristic algorithm (NSGA-II) to solve the model with actual data from a case study of the steel industry in Iran. The results obtained from the model, solving and validating, compared with actual data indicated that the model could optimize the objectives seamlessly and determine the amount and location of the necessary facilities for the steel industry more appropriately.This article belongs to the Special Issue Uncertain Multi-Criteria Optimization Problem

Gestão de Recursos Finitos em Empresas

The present work has as goal aiding decision makers, researchers, enterprises and practitioners by developing a proper literature review as a base for comparison among multiple-criteria decision making methods in finite resources management according to each of the most important areas of a business environment. Efficient resource management decision making in companies impacts its value creation capability and, therefore, its competitiveness and ultimate success. The methodology for paper research follows the PRISMA flow diagram, for correct paper filtrations according to the set of criteria stablished in alignment with the thesis goal. The papers included in the study are any that employ multiple-criteria decision making methods in their pure forms, in combination with each other forming hybrids, or in combination with other mathematical techniques for solving decision making problems across five major areas of a company’s body. The five major areas are: (1) Supply Chain Management and Logistics; (2) Environmental Management; (3) Business and Marketing Management; (4) Design, Engineering and Manufacturing Systems; and (5) Human Resources Management. The 204 final papers are presented separated by their corresponding application areas, ordered by number of citations, which is used as a measure of their scientific community relevance. They are also classified by, author, nationality, journal, year, type of research and methods used. All collected data is used for quantitative statistical analysis, with which is possible to collect more in-depth information on the literature research. Focused comments on the main methods are also present in this work, with observations made on the many applications and variations each of them had throughout the articles in the research. The AHP and TOPSIS approaches, either with their fuzzy set variations are by far the most popular methods in the referred applications. However, besides them other 51 MCDM or other mathematical techniques are employed in many different combinations and approaches, bringing a very interesting diversity to the study that is very useful for it to be used as a base for comparison among methods. A total number of 111 journals and authors and co-authors of 41 nationalities are involved in the publications between 2012 and 2018, with more than half of papers coming from either India, Turkey or Iran. Many other results are obtained, bringing the readers different perspectives on the subject. This paper contributes to the body of knowledge with a great and insightful overview on MCDM methods application in aiding in challenges part of a business environment, so that companies can better manage their resources and be more prosperous. It is a vast database that allows many comparisons and evaluations, offering more analysis than the standard literature review articles.O presente trabalho tem como objetivo auxiliar os tomadores de decisão, pesquisadores e profissionais, ao desenvolver uma revisão bibliográfica adequada como base para comparação entre os métodos de decisão multicritério na gestão de recursos finitos de acordo com cada uma das áreas mais importantes de um ambiente de negócios. A tomada eficiente de decisões de gestão de recursos nas empresas afeta sua capacidade de criação de valor e, portanto, sua competitividade e sucesso finais. A metodologia da investigação baseou-se na metodologia PRISMA, para a correta filtração das publicações de acordo com o conjunto de critérios estabelecidos, em alinhamento com o objetivo da tese. Os artigos incluídos no estudo são aqueles que apresentam métodos de decisão com critérios múltiplos em suas formas puras, em combinação uns com os outros ao formar híbridos, ou com outras técnicas matemáticas para resolver problemas em cinco áreas principais das empresas. As cinco áreas são: (1) Gestão da Cadeia de Suprimentos e Logística; (2) Gestão Ambiental; (3) Gestão de Negócios e Marketing; (4) Sistemas de Projeto, Engenharia e Manufatura; e (5) Gestão de Recursos Humanos. Os 204 artigos finais são apresentados de acordo com as áreas de aplicação correspondentes, ordenadas por número de citações, que são usadas como uma medida de sua relevância na comunidade científica. Eles são, ainda, classificados por autor, nacionalidade, revista, ano, tipo de pesquisa e métodos utilizados. Todos os dados coletados são utilizados para análise estatística quantitativa, com a qual é possível recolher informações mais aprofundadas sobre a pesquisa bibliográfica. São realizados comentários sobre os principais métodos e as maneiras que foram apresentados ao longo do estudo de todos os artigos durante a pesquisa. As abordagens AHP e TOPSIS, com suas variações em conjuntos difusos ou fuzzy, são de longe os métodos mais populares nas aplicações referidas. No entanto, além destes, outros 51 MCDM e outras técnicas são utilizadas em muitas combinações e abordagens, trazendo uma diversidade muito interessante para o estudo, servindo de base para comparação dos métodos. Um total de 111 revistas e autores e coautores de 41 nacionalidades estão envolvidos nas publicações entre 2012 e 2018, com mais de metade dos artigos provenientes da Índia, Turquia ou Irão. Estes e outros resultados levam aos leitores diferentes perspectivas sobre o assunto. Este documento contribui para o estado da arte, com um conhecimento geral excelente e perspicaz sobre a aplicação de métodos MCDM para ajudar nos desafios de um ambiente de negócios, para que as empresas possam melhor gerenciar seus recursos e serem mais prósperas. É um vasto banco de dados que permite muitas comparações e avaliações, oferecendo mais análises do que os artigos de revisão de literatura padrão

Analytic Hierarchy Process and Supply Chain Management: A Bibliometric Study

AbstractA comparative study was used to outline the literature in the research topic. This paper aims to present a bibliometric study ofmulti-criteria decision-making methods most applied in publications from 1990 to 2014. Our research presented relations of papers published in the Web of Science Core Collection, regarding the following keywordsAnalytic Hierarchy Process and Supply Chain. The research evidenced that the Analytic Hierarchy Process has been the method mostapplied in publications from 1993. It also showed the analysis of the predecessor and successor citation network for the selected publications under topics as supplier selection, supply development, performance measurement and value chain through the CitNetExplore software

Supply Chain

Traditionally supply chain management has meant factories, assembly lines, warehouses, transportation vehicles, and time sheets. Modern supply chain management is a highly complex, multidimensional problem set with virtually endless number of variables for optimization. An Internet enabled supply chain may have just-in-time delivery, precise inventory visibility, and up-to-the-minute distribution-tracking capabilities. Technology advances have enabled supply chains to become strategic weapons that can help avoid disasters, lower costs, and make money. From internal enterprise processes to external business transactions with suppliers, transporters, channels and end-users marks the wide range of challenges researchers have to handle. The aim of this book is at revealing and illustrating this diversity in terms of scientific and theoretical fundamentals, prevailing concepts as well as current practical applications

Partner selection in agile supply chains: A fuzzy intelligent approach

Partner selection is a fundamental issue in supply chain management as it contributes significantly to overall supply chain performance. However, such decision-making is problematic due to the need to consider both tangible and intangible factors, which cause vagueness, ambiguity and complexity. This paper proposes a new fuzzy intelligent approach for partner selection in agile supply chains by using fuzzy set theory in combination with radial basis function artificial neural network. Using these two approaches in combination enables the model to classify potential partners in the qualification phase of partner selection efficiently and effectively using very large amounts of both qualitative and quantitative data. The paper includes a worked empirical application of the model with data from 84 representative companies within the Chinese electrical components and equipment industry, to demonstrate its suitability for helping organisational decision-makers in partner selection