IoT-based milk-run routing for manufacturing system: an application case in an automotive company

AbstractThe Internet of Things (IoT) provides new opportunities to improve manufacturing lines' performance and in-plant logistic processes. The digital milk-run system represents the new frontier to optimize material handling strategies but is still not fully exploited to address material distribution depending on the time slots required by the manufacturing lines. Therefore, to fill this gap, this paper investigates the actual integration of the milk-run system with an IoT system. An analytical model for planning a dynamic routing strategy for tugger trains to deliver the materials to different workstations of a production line has been developed. The proposed model provides a materials distribution consistent with the time slot required by the manufacturing line, ensuring the minimisation of the total distance of the routes. An algorithm developed in Python is proposed to solve the NP-hard problem (nondeterministic polynomial time problem). The model has been applied to a real case of a worldwide automotive company to validate and prove its efficacy and efficiency. Indeed, compared to the current in-plant logistic strategy, (i) the inventory stock of each workstation was ensured, (ii) the average utilization rate of the tugger trains' fleet was improved, and (iii) the daily path was minimized.KEYWORDS: Internet of thingsindustry 4.0in-plant logisticsmaterial handling strategymilk-run system Author contributionsConceptualization, F.F.; methodology, F.F.; software, F.F.; validation, F.F., G.M. and S.D.; formal analysis, F.F.; investigation, F.F.; resources, F.F.; data curation, F.F.; writing – original draft preparation, F.F.; writing – review and editing, S.D. and C.S.; visualization, S.D. and C.S.; supervision, G.M. All authors have read and agreed to the published version of the manuscript.Data availability statementThe data that support the findings of this study are available from the corresponding author, F.F., upon reasonable request.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationNotes on contributorsFrancesco FacchiniFrancesco Facchini Assistant professor at the Polytechnic University of Bari (Italy), Dept. of Mechanics, Mathematics, and Management. Member of the Board of Professors of the PhD Course on 'Mechanical and management engineering'. Professor of 'Operations Management' for a master's degree in Management Engineering and professor of 'Industrial Logistics' for a bachelor's degree in Management Engineering. His research fields include Sustainable logistics, ergonomics assessment in industrial work environments, and simulation models based on Artificial Neural Networks. He is the author of more than 70 scientific publications.Giorgio MossaGiorgio Mossa Full Professor of Industrial Systems Engineering at the Polytechnic University of Bari (Italy). He has been involved as Principal Investigator in many research projects financially supported by 'EU', 'Italian Ministry of Education, University and Research', 'Apulia Region' and national and international companies. Main research topics have been: design and management of industrial systems and supply chains, operations and maintenance, sustainability of products and of production systems, human performance modelling. Professor of Operations Management, Environmental Management of Production Systems, and Safety of Industrial Plants at the Polytechnic University of Bari. Currently responsible for the Master Degree (M.Sc.) in Industrial Engineering and Management and member of the Board of Professor of the PhD Course on 'Mechanical and management engineering' at the Polytechnic University of Bari. He is the author of more than 100 scientific publications.Claudio SassanelliClaudio Sassanelli Claudio Sassanelli is Assistant Professor at Politecnico di Bari, Department of Mechanics, Mathematics and Management and Senior Research Fellow at Ecole des Ponts Business School of Ecole des Ponts ParisTech. He received his two master degrees in Management and Civil Engineering from Politecnico di Bari, respectively in 2010 and 2013, and his PhD in Management, Economics and Industrial Engineering from Politecnico di Milano in 2017, also holding visiting researcher positions at Tokyo Metropolitan University (TMU) and Universidade de Sao Paulo (USP). His main research interest is Product-Service System (PSS) design, specifically addressing to Product Lifecycle Management (PLM), Design for X (DfX) approaches, and Circular Economy and Industry 4.0 paradigms. To advance these research domains, he manages special issues in international journals as guest editor, and disseminates his research being editor of one book and co-author of around 90 publications in international journals, international conferences proceedings and book chapters in the field. He is member of the IFIP WG 5.1 and of the editorial board of the journals Sustainability MDPI, Frontiers in Sustainability, Frontiers in Environmental Science, and Academia Engineering. He has a 10-year experience in research, industrial and European research and innovation action projects. He carries out teaching activities in courses on production systems (environmental management, design and management, industrial technologies), and quality design and management, at Politecnico di Bari, Politecnico di Milano, SUPSI and LIUC Universita' Cattaneo.Salvatore DigiesiSalvatore Digiesi Associate Professor of Mechanical Plants and Design and Management of Industrial Systems of first cycle and second cycle curricula in Mechanical Engineering, respectively, at the Polytechnic of Bari. Member of the Board of Professor of the PhD Course on 'Industry 4.0' at the Polytechnic of Bari. He has been involved as researcher in many research projects financially supported by 'EU', 'Italian Ministry of Education, University and Research', 'Apulia Region' and national and international companies. Main research topics are: sustainable logistics, renewable energy, design and management of industrial systems and supply chains, human performance modeling, and design and management of networks of public services in a 'smart city'. He is author of more than 60 scientific publications.