Investigation of degradation and upgradation models for flexible unit systems: a systematic literature review

Research on flexible unit systems (FUS) with the context of descriptive, predictive, and prescriptive analysis have remarkably progressed in recent times, being now reinforced in the current Industry 4.0 era with the increased focus on integration of distributed and digitalized systems. In the existing literature, most of the work focused on the individual contributions of the above mentioned three analyses. Moreover, the current literature is unclear with respect to the integration of degradation and upgradation models for FUS. In this paper, a systematic literature review on degradation, residual life distribution, workload adjustment strategy, upgradation, and predictive maintenance as major performance measures to investigate the performance of the FUS has been considered. In order to identify the key issues and research gaps in the existing literature, the 59 most relevant papers from 2009 to 2020 have been sorted and analyzed. Finally, we identify promising research opportunities that could expand the scope and depth of FUS.The project is funded by the Department of Science and Technology, Science & Engineering Research Board (DST-SERB), Statutory Body Established through an Act of Parliament: SERB Act 2008, Government of India with Sanction Order No ECR/2016/001808, and also by FCT—Fundação para a Ciência e Tecnologia through the R&D Units Project Scope: UIDB/00319/2020

Increase the adoption of Agent-based Cyber-Physical Production Systems through the Design of Minimally Invasive Solutions

During the last few years, many approaches were proposed to offer companies the ability to have dynamic and flexible production systems. One of the conventional ap-proaches to solving this problem is the implementation of cyber-physical production sys-tems using multi-agent distributed systems. Although these systems can deal with several challenges faced by companies in this area, they have not been accepted and used in real cases. In this way, the primary objective of the proposed work is to understand the chal-lenges usually found in the adoption of these solutions and to develop a strategy to in-crease their acceptance and implementation. Thus, the document focuses on the design and development of cyber-physical produc-tion systems based on agent approaches, requiring minimal changes in the existing pro-duction systems. This approach aims of reducing the impact and the alterations needed to adopt those new cyber-physical production systems. Clarifying the subject, the author presents a definition of a minimal invasive agent-based cyber-physical production system and, the functional requirements that the designers and developers must respect to imple-ment the new software. From these functional requirements derived a list of design princi-ples that must be fulfilled to design and develop a system with these characteristics. Subsequently, to evaluate solutions that aim to be minimally invasive, an evaluation model based on a fuzzy inference system is proposed, which rank the approaches accord-ing to each of the design principles and globally. In this way, the proposed work presents the functional requirements, design principles and evaluation model of minimally invasive cyber-physical production systems, to increase the adoption of such systems

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

A knowledge based approach to integration of products, processes and reconfigurable automation resources

The success of next generation automotive companies will depend upon their ability to adapt to ever changing market trends thus becoming highly responsive. In the automotive sector, the assembly line design and reconfiguration is an especially critical and extremely complex job. The current research addresses some of the aspects of this activity under the umbrella of a larger ongoing research project called Business Driven Automation (BDA) project. The BDA project aims to carry out complete virtual 3D modeling-based verifications of the assembly line for new or revised products in contrast to the prevalent practice of manual evaluation of effects of product change on physical resources. [Continues.