An Overview of Next-generation Manufacturing Execution Systems:How important is MES for Industry 4.0?

The purpose of this paper is to understand the evolution of manufacturing execution systems (MES) in the digital transformation era. Theoretical propositions made on MES (based on literature survey) were empirically examined using three case studies in Danish companies. Findings gave an overview of Industry 4.0 ready MES and identified its role in factories of the future. It is a first attempt to analyze the concepts behind next-generation MES to give a primer on ‘MES as a digital twin', via first iteration of results from cross-case synthesis of collected data. The paper also maps the current MES research pertaining to Industry 4.0 into key groups to highlight its significance in digital manufacturing

Multi-agent Manufacturing Execution System (MES):Concept, architecture & ML algorithm for a smart factory case

Smart factory of the future is expected to support interoperability on the shop floor, where information systems are pivotal in enabling interconnectivity between its physical assets. In this era of digital transformation, manufacturing execution system (MES) is emerging as a critical software tool to support production planning and control while accessing the shop floor data. However, application of MES as an enterprise information system still lacks the decision support capabilities on the shop floor. As an attempt to design intelligent MES, this paper demonstrates one of the artificial intelligence (AI) applications in the manufacturing domain by presenting a decision support mechanism for MES aimed at production coordination. Machine learning (ML) was used to develop an anomaly detection algorithm for multi-agent based MES to facilitate autonomous production execution and process optimization (in this paper switching the machine off after anomaly detection on the production line). Thus, MES executes the ‘turning off’ of the machine without human intervention. The contribution of the paper includes a concept of next-generation MES that has embedded AI, i.e., a MES system architecture combined with machine learning (ML) technique for multi-agent MES. Future research directions are also put forward in this position paper

Design choices for next-generation IIoT-connected MES/MOM:An empirical study on smart factories

The role of enterprise information systems is becoming increasingly crucial for improving customer responsiveness in the manufacturing industry. However, manufacturers engaged in mass customization are currently facing challenges related to implementing Industrial Internet of Things (IIoT) concepts of Industry 4.0 in order to increase responsiveness. In this article, we apply the findings from a two-year design science study to establish the role of manufacturing execution systems/manufacturing operations management (MES/MOM) in an IIoT-enabled brownfield manufacturing enterprise. We also present design recommendations for developing next-generation MES/MOM as a strong core to make factories smart and responsive. First, we analyze the architectural design challenges of MES/MOM in IIoT through a selective literature review. We then present an exploratory case study in which we implement our homegrown MES/MOM data model design based on ISA 95 in Aalborg University's Smart Production Lab, which is a reconfigurable cyber-physical production system. This was achieved through the use of a custom module for the open-source Odoo ERP platform (mainly version 14). Finally, we enrich our case study with three industrial design demonstrators and combine the findings with a quality function deployment (QFD) method to determine design requirements for next-generation IIoT-connected MES/MOM. The results from our QFD analysis indicate that interoperability is the most important characteristic when designing a responsive smart factory, with the highest relative importance of 31% of the eight characteristics we studied

Securing IT/OT Links for Low Power IIoT Devices:Design considerations for industry 4.0

Manufacturing is facing a host of new security challenges due to the convergence of information technology (IT) and operational technology (OT) in the industry. This article addresses the challenges that arise due to the use of low power Industrial Internet of Things (IIoT) devices in modular manufacturing systems of Industry 4.0. First, we analyze security challenges concerning the manufacturing execution system (MES) and programmable logic controllers (PLC) in IIoT through a selective literature review. Second, we present an exploratory case study to determine a protocol for cryptographic key management and key exchange suitable for the Smart Production Lab of Aalborg University (a learning cyber-physical factory). Finally, we combine the findings of the case study with a quality function deployment (QFD) method to determine design requirements for Industry 4.0. We identify specific requirements from both the high-level domain of factory capabilities and the low-level domain of cryptography and translate requirements between these domains using a QFD analysis. The recommendations for designing a secure smart factory focus on how security can be implemented for low power and low-cost IIoT devices. Even though there have been a few studies on securing IT to OT data exchange, we conclude that the field is not yet in a state where it can be applied in practice with confidence

Exploring Reconfigurability in Manufacturing through IIoT Connected MES/MOM

This paper explores the role of manufacturing execution systems (MES) with ISA 95 functionalities for the reconfigurability in a manufacturing enterprise. The work is aimed at supporting digitalization based on Industry 4.0 and the Industrial Internet of Things (IIoT) concepts. For this, we use the quality function deployment method to link ISA 95 MES functionalities and reconfigurability needs, based on a case example of a cyber-physical factory (AAU Smart Lab). Accordingly, we present a framework to assess reconfigurability for smart factory development. The paper identifies reconfigurability approaches using IIoT connected MES/MOM for tackling severe market disruptions (e.g. the one caused by the ongoing COVID-19 pandemic)

How Important are Digital Technologies for Urban Food Security? A Framework for Supply Chain Integration using IoT

This paper aims to understand the role of digital technologies in food system innovations for healthy food access and waste reduction. It seeks to expand the knowledge of commercial food system interventions from the industrial supply side for improving public and planetary health. For this, we review the literature on urban food supply chains and synthesize the findings (from 33 screened articles) into thematic clusters. The first iteration of the review gives an overview of food supply chain problems and possible Industry 4.0-based solutions. Four technology intervention opportunities for integrated supply chains emerge from the literature, namely digital platforms, enterprise information systems, traceability systems, and blockchain. Findings indicate limited empirical research on supply chain digitalization for healthy food access. Therefore, this position paper presents a framework for supply chain integration in urban food systems, emphasizing digital technology interventions and the research directions for food supply chain digitalization