Abstract
Due to the transformations stemming from Industry 4.0, many organizations are adopting technologies to make their factories more connected and interoperable. Enterprise interoperability is characterized by the ability to exchange information between one or more systems, departments or companies. The classic interpretation of EIA (Enterprise Interoperability Assessment) proposes concerns and barriers that characterize the constraints to obtain an ideal organizational performance. The literature is insufficient to present approaches that relate the implementation of new technologies with other business domains. Thus, to keep the company competitive through waste elimination practices and optimization processes, the Lean Manufacturing (LM) Production system becomes a source of performance indicators, which will be parameters for the adoption of technologies that must meet interoperability requirements. This work proposes a framework to obtain a technology prioritization model based on a diagnostic approach considering LM performance indicators within the scope of Interoperability in a company of the metal mechanic sector. Firstly, the PROMETHEE II multi-criteria decision analysis (MCDA) method will be used to identify the technologies that provide good results to the LM performance indicators of the organization. The identified technologies will, secondly, be evaluated using the ELECTRE I method, which will indicate those that best meet the organization's needs, jointly considering LM criteria and interoperability requirements. The results show that the technologies related to data synchronization, tracking, integration, process management, schedule monitoring, kanban update, and standardized interfaces are decisive, since they provide good results to the LM performance indicators and relate them to the organization's interoperability requirements.
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da Rocha Moro, M., de Freitas Rocha Loures, E., Neto, A.A., Ramos, L.F.P., Santos, V., do Amaral, L.M.B. (2023). Prioritization of Industry 4.0 Technologies Based on Diagnosis and Performance Indicators Associated with Lean Manufacturing Under Interoperability Requirements. In: Kim, KY., Monplaisir, L., Rickli, J. (eds) Flexible Automation and Intelligent Manufacturing: The Human-Data-Technology Nexus. FAIM 2022. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-17629-6_42
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