Smart Master Production Schedule for the Supply Chain: A Conceptual Framework

Julio C Serrano-Ruiz,Raúl Poler,Josefa Mula

doi:10.3390/computers10120156

Julio C Serrano-Ruiz, Raúl Poler + Show 1 more

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https://doi.org/10.3390/computers10120156

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Abstract

Risks arising from the effect of disruptions and unsustainable practices constantly push the supply chain to uncompetitive positions. A smart production planning and control process must successfully address both risks by reducing them, thereby strengthening supply chain (SC) resilience and its ability to survive in the long term. On the one hand, the antidisruptive potential and the inherent sustainability implications of the zero-defect manufacturing (ZDM) management model should be highlighted. On the other hand, the digitization and virtualization of processes by Industry 4.0 (I4.0) digital technologies, namely digital twin (DT) technology, enable new simulation and optimization methods, especially in combination with machine learning (ML) procedures. This paper reviews the state of the art and proposes a ZDM strategy-based conceptual framework that models, optimizes and simulates the master production schedule (MPS) problem to maximize service levels in SCs. This conceptual framework will serve as a starting point for developing new MPS optimization models and algorithms in supply chain 4.0 (SC4.0) environments.

Highlights

Since artificial intelligence began to make its way into almost all the sectors of today’s society, the adjectives intelligent or smart have become commonplace to describe a myriad of entities which are, in one way or another, endowed with the ability to react to changes in the environment to establish optimal operating conditions by themselves
For a supply chain 4.0 (SC4.0), understood as the supply chain (SC) that is reorganized by using the design principles and enabling technologies of the Industry 4.0 (I4.0) spectrum [1], it seems appropriate to link the intelligent or smart attributes with SC abilities to overcome the risks that it faces and survive as the main proof of its capability to respond to challenging changes in the environment and to achieve optimal operating conditions
Not many examples appear in the literature that show the benefits of the digital twin (DT) in the specific master production schedule (MPS) field [18], but they can be found in many other SC fields, such as real-time monitoring and control [62], risk management [13], recovery from disruption [65], SCs’ resilience to disruption [66], planning verifications related to demand forecasting, aggregate planning, and inventory planning [10]

Summary

Introduction

Since artificial intelligence began to make its way into almost all the sectors of today’s society, the adjectives intelligent or smart have become commonplace to describe a myriad of entities which are, in one way or another, endowed with the ability to react to changes in the environment to establish optimal operating conditions by themselves. For a supply chain 4.0 (SC4.0), understood as the supply chain (SC) that is reorganized by using the design principles and enabling technologies of the Industry 4.0 (I4.0) spectrum [1], it seems appropriate to link the intelligent or smart attributes with SC abilities to overcome the risks that it faces and survive as the main proof of its capability to respond to challenging changes in the environment and to achieve optimal operating conditions. Along these lines, and regardless of whether causes are natural, economic, political or technological, disruption is the most significant risk that an SC faces in the short and mid terms. An SC4.0, such as a smart SC, should be resilient and sustainable

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