Human resource allocation problem in the Industry 4.0: A reference framework. (July 2022)

• Record Type: Journal Article
• Authors: Grillo, H.; Alemany, M.M.E.; Caldwell, E.
• Is Part Of: Computers & industrial engineering. Volume 169(2022)
• Publication Date: 2022-07
• Subjects: Human Resource Allocation Problem -- Mathematical modelling -- Linear programming -- Flexible workforce -- Human Resource in Industry 4.0; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108110
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: HRAP needs to be updated to adapt to Industry 4.0 and generalize to HRAP-4.0. HRAP-4.0 requires a flexible workforce for better and more complex assignations. Reference Framework for building HRAP-4.0 linear models based on building blocks. Human resources in Industry 4.0 should be part of the Cyber-Physical Systems design. Cyber-Physical Systems collaborate with people for better productivity rates. Abstract: The Human Resource Allocation Problem (HRAP) is a well-known mathematical modeling type where a set of tasks should be assigned to a group of operators. As the smart production system brought by Industry 4.0 (I4.0) requires aligning new technologies with the human perspective, existing HRAP models should be revised and adapted to this new context. Therefore, this paper aims to design a complete proposal to support the modeling, implementation, and dynamic use of the HRAP in I4.0 called HRAP-4.0. To do so, first, the I4.0 factors that affect the HRAP are identified to revise to what extent existing models in the literature address them. To bridge gaps, this paper proposes contributions in two areas: mathematical models and methodological aspects. First, new mathematical formulations of optimization strategies (objectives) and constraints are modeled to include the I4.0 factors in a modular and reusable way, generating HRAP-4.0 model building block categories. Then a reference framework to support the formulation of HRAP-4.0 adapted to specific I4.0 situations based on the categories above is presented. Last, an implementation methodology is proposed to integrate the framework into a real I4.0 context and use the resulting HRAP-4.0 models in a dynamic environment. The reference framework comprises two decision trees to support selecting the most suitable optimization strategies (objectives) and constraints categories for the HRAP-4.0 under study. It collects the existing model categories in the literature, plus the new ones related to I4.0 herein developed. They are all essential within the cyber-physical systems (CPS) frame, which is the base of I4.0. The proposed HRAP-4.0, thus, becomes the new original tool for assigning tasks to people in the modern production system.