Daniel Alejandro Rossit, Diego Gabriel Rossit, Adrián Andrés Toncovich, Fernando Abel Tohmé
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Thanks to the participation and commitment of the attendees, the congress was carried out successfully, allowing many young researchers to participate in an international congress, in a year in which these opportunities were scarce. The ICPR-Americas meeting space provided them with the opportunity to share their work as well as to exchange ideas and points of view, all in the usual cordial atmosphere of the ICPR-Americas conferences.</p><p>The main aim of these conferences is to explore the improvement and development of production capacities and to seek knowledge about how to enhance production efficiency in a wide range of economic sectors. During the conference, a total of 245 papers were presented. More than 900 authors submitted their contributions to ICPR-Americas 2020 from different regions of the world, mainly from the Americas but also from Europe and Asia, ensuring a rich international atmosphere to the conference. The number of registrations at the conference surpassed 300. The presentations were arranged in 15 different special sessions and a central track. The authors of carefully selected papers presented at the conference were invited to extend and submit them to this Special Issue. These articles went through the journal's own reviewing process and after completing this phase, those high-quality submissions focussing on the decision-making process in production environments were selected for publication in this Special Issue.</p><p>In an increasingly competitive world, decision-making processes are key drivers of production systems, since they allow translating clients' demands into production actions, aiming to achieve organizational efficiency. In recent years, decision processes have been greatly enhanced by the incorporation of information technologies that allow integrating the different functionalities of the organizations, leading to more agile and flexible decision-making processes. Information technologies are useful to digitise all the information associated with the production process by ensuring the availability of this information in real time for the different sectors of companies, increasing response capacity and speeding up the decision-making processes. Moreover, the decisions and action plans generated using the information provided by the shop floor in the different business functions become immediately visible for the rest of the business functions of a company, enhancing transparency. All these aforementioned aspects contribute to the minimisation of costs and to increase the productivity of the company.</p><p>This Special Issue presents contributions to three very important areas related to the development of these technologies: (i) the use of data, drawn from production machines, in the decision-making process, (ii) the generation of product mixes in production, and (iii) the design of company architectures based on digital technologies.</p><p>With regard to the first topic addressed, the first paper of this Special Issue, entitled “<i>Performance measurement based on machines data: Systematic literature review</i>”, presents a careful bibliometric study of the literature on how shop-floor data is used in decision-making processes. In this review, Hidalgo Martins, Gleison; Deschamps, Fernando; Pereira Detro, Silvana and Deivid Valle, and Pablo use a PROKNOW-C (Knowledge Development Process-Constructivist) approach, which allows the generation of a Bibliographic Portfolio to structure the results of the reviewing process.</p><p>In “<i>Use of Goal Programming and the Fuzzy Analytical Hierarchy Process to obtain the product mix</i>”, Zárate, Claudia; Esteban, Alejandra; Berardi, María and Ledesma Frank, Keila develop a fuzzy mathematical model with a weighted goal programming approach. The model represents the production planning process involved in selecting a product mix maximizing three metrics: the expected profit, the use of resources, and the output. An Analytical Hierarchy Process model is used to define the weights of the different metrics.</p><p>In the third and last work, entitled “<i>Applying a Decision Model Based on Multi Criteria Decision Making</i> <i>Methods to Evaluate the Influence of Digital Transformation Technologies on Enterprise Architecture Principles</i>”, Hannemann de Freitas, Izabelle; Rodrigues, Sarah; Rocha Loures, Eduardo; Deschamps, Fernando and Cestari, and Jose review the literature analysing the main aspects of the digital transformation affecting the companies' architecture. The authors implement different multi-criteria methods, such as DEMATEL and PROMETHEE, which allow the identification of the key technologies that allow redesigning the architectures of firms.</p>","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"4 2","pages":"71-73"},"PeriodicalIF":2.5000,"publicationDate":"2022-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12054","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Collaborative Intelligent Manufacturing","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/cim2.12054","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0
Abstract
From December 9 to 11, 2020, the “Xth International Conference of Production Research-Americas” (ICPR-Americas 2020) was held virtually in Bahía Blanca, Argentina. This conference was coordinated by a local organising committee and was sponsored by the International Foundation for Production Research. The ICPR-Americas series of conferences aim to exchange experiences and foster collaborative work among researchers and professionals from the Americas and the Caribbean region. This was the first time that the conference was held in Argentina.
ICPR-Americas 2020 was held in virtual mode due to the COVID-19 pandemic. Thanks to the participation and commitment of the attendees, the congress was carried out successfully, allowing many young researchers to participate in an international congress, in a year in which these opportunities were scarce. The ICPR-Americas meeting space provided them with the opportunity to share their work as well as to exchange ideas and points of view, all in the usual cordial atmosphere of the ICPR-Americas conferences.
The main aim of these conferences is to explore the improvement and development of production capacities and to seek knowledge about how to enhance production efficiency in a wide range of economic sectors. During the conference, a total of 245 papers were presented. More than 900 authors submitted their contributions to ICPR-Americas 2020 from different regions of the world, mainly from the Americas but also from Europe and Asia, ensuring a rich international atmosphere to the conference. The number of registrations at the conference surpassed 300. The presentations were arranged in 15 different special sessions and a central track. The authors of carefully selected papers presented at the conference were invited to extend and submit them to this Special Issue. These articles went through the journal's own reviewing process and after completing this phase, those high-quality submissions focussing on the decision-making process in production environments were selected for publication in this Special Issue.
In an increasingly competitive world, decision-making processes are key drivers of production systems, since they allow translating clients' demands into production actions, aiming to achieve organizational efficiency. In recent years, decision processes have been greatly enhanced by the incorporation of information technologies that allow integrating the different functionalities of the organizations, leading to more agile and flexible decision-making processes. Information technologies are useful to digitise all the information associated with the production process by ensuring the availability of this information in real time for the different sectors of companies, increasing response capacity and speeding up the decision-making processes. Moreover, the decisions and action plans generated using the information provided by the shop floor in the different business functions become immediately visible for the rest of the business functions of a company, enhancing transparency. All these aforementioned aspects contribute to the minimisation of costs and to increase the productivity of the company.
This Special Issue presents contributions to three very important areas related to the development of these technologies: (i) the use of data, drawn from production machines, in the decision-making process, (ii) the generation of product mixes in production, and (iii) the design of company architectures based on digital technologies.
With regard to the first topic addressed, the first paper of this Special Issue, entitled “Performance measurement based on machines data: Systematic literature review”, presents a careful bibliometric study of the literature on how shop-floor data is used in decision-making processes. In this review, Hidalgo Martins, Gleison; Deschamps, Fernando; Pereira Detro, Silvana and Deivid Valle, and Pablo use a PROKNOW-C (Knowledge Development Process-Constructivist) approach, which allows the generation of a Bibliographic Portfolio to structure the results of the reviewing process.
In “Use of Goal Programming and the Fuzzy Analytical Hierarchy Process to obtain the product mix”, Zárate, Claudia; Esteban, Alejandra; Berardi, María and Ledesma Frank, Keila develop a fuzzy mathematical model with a weighted goal programming approach. The model represents the production planning process involved in selecting a product mix maximizing three metrics: the expected profit, the use of resources, and the output. An Analytical Hierarchy Process model is used to define the weights of the different metrics.
In the third and last work, entitled “Applying a Decision Model Based on Multi Criteria Decision MakingMethods to Evaluate the Influence of Digital Transformation Technologies on Enterprise Architecture Principles”, Hannemann de Freitas, Izabelle; Rodrigues, Sarah; Rocha Loures, Eduardo; Deschamps, Fernando and Cestari, and Jose review the literature analysing the main aspects of the digital transformation affecting the companies' architecture. The authors implement different multi-criteria methods, such as DEMATEL and PROMETHEE, which allow the identification of the key technologies that allow redesigning the architectures of firms.
期刊介绍:
IET Collaborative Intelligent Manufacturing is a Gold Open Access journal that focuses on the development of efficient and adaptive production and distribution systems. It aims to meet the ever-changing market demands by publishing original research on methodologies and techniques for the application of intelligence, data science, and emerging information and communication technologies in various aspects of manufacturing, such as design, modeling, simulation, planning, and optimization of products, processes, production, and assembly.
The journal is indexed in COMPENDEX (Elsevier), Directory of Open Access Journals (DOAJ), Emerging Sources Citation Index (Clarivate Analytics), INSPEC (IET), SCOPUS (Elsevier) and Web of Science (Clarivate Analytics).