Conceptual and optimisation modelling for lean supply chain planning in industry 4.0

Abstract

Innovation in working methods with new lean, sustainable and resilient production systems, as well as effective technology management, are current trends to improve performance in organisations. This PhD thesis investigates the theoretical contributions and formulates a conceptual model with the use of lean manufacturing (LM) and Industry 4.0 (I4.0) tools for production planning processes in supply chains (SCs). In addition, optimisation is employed as an enabling technology of I4.0 to develop the proposed solution. The applied methodology is bibliographic, exploratory and experimental; operational research techniques, data standardisation and case studies in industrial companies are applied. As a starting point, the existing literature related to LM and I4.0 technologies in the SC context is reviewed. Then a conceptual model, known as LSCP 4.0, is designed to facilitate decision making at the strategic, tactical and operational decision levels. It is a structured relation among lean, agile, sustainable, resilient and flexible paradigms to improve SCs' performance via the application of I4.0 enabling technologies. Based on this, an integer-mixed linear optimisation mathematical model, termed LSCP 4.0, is proposed to maximise profits and to simultaneously plan production, material inventory and finished goods by satisfying the demand from forecasts and firm orders in a five-tier SC. Novel just-in-time (JIT) production and material requirements planning (MRP) approaches are combined. Both models for LSCP 4.0, i.e., conceptual and mathematical, are validated in real case studies from the footwear industry. The use of another I4.0 enabling technology, such as cloud computing, is considered to address the problem of information exchange between SC nodes. Thus a standardised data model for collaborative manufacturing in the cloud applied to the footwear industry is proposed.