Smart Cyber-Physical Manufacturing: Extended and Real-Time Optimization of Logistics Resources in Matrix Production

Ágota Bányai,Norge Isaias Coello Machado,Elke Glistau,Péter Tamás,Faiza Manzoor,Béla Illés,Tamás Bányai

doi:10.3390/app9071287

Abstract

In the context of Industry 4.0, the matrix production concept represents revolutionary solutions from a technological and logistics point of view. In a matrix production system, flexible, configurable production and assembly cells are arranged in a grid layout, and the in-plant supply is based on autonomous vehicles. Adaptable and flexible material handling solutions are required to perform the dynamically changing supply-demands of standardized and categorized manufacturing and assembly cells. Within the frame of this paper, the authors describe the in-plant supply process of matrix production and the optimization potential in these processes. After a systematic literature review, this paper introduces the structure of matrix production as a cyber-physical system focusing on logistics aspects. A mathematical model of this in-plant supply process is described including extended and real-time optimization from routing, assignment, and scheduling points of view. The optimization problem described in the model is an NP-hard problem. There are no known efficient analytical methods to find the best solution for this kind of problem; therefore, we use heuristics to find a suitable solution for the above-described problem. Next, a sequential black hole–floral pollination heuristic algorithm is described. The scenario analysis, which focuses on the clustering and routing aspects of supply demands in a matrix production system, validates the model and evaluates its performance to increase cost-efficiency and warrants environmental awareness of the in-plant supply in matrix production.

Highlights

Production companies have to apply the solutions of cyber-physical systems to improve their availability, efficiency, reliability, and productivity
Sci. 2019, 9, 1287 of Internet of Things (IoT) solutions leads to hyperconnected value chains, where manufacturing and the related supply chain and logistics processes are operating in a cyber-physical environment
In spite of the small size of the demonstrated problems, these results show problems, these results show that the hole proposed method using black hole and floral pollination that the proposed method using black and floral pollination algorithms performs better than algorithms performs better thanThe the conventional models.can

Summary

Introduction

Production companies have to apply the solutions of cyber-physical systems to improve their availability, efficiency, reliability, and productivity. The ever-changing manufacturing industry requires the improvement of these attributes. Statistical surveys suggest that by the end of 2019, about 75% of large manufacturing companies will update their operations with Internet of Things solutions [1] and transform their conventional manufacturing environment to cyber-physical systems. Sci. 2019, 9, 1287 of IoT solutions leads to hyperconnected value chains, where manufacturing and the related supply chain and logistics processes are operating in a cyber-physical environment

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Results

Conclusion