Energy efficiency in discrete-manufacturing systems: insights, trends, and control strategies

Since the depletion of fossil energy sources, rising energy prices, and governmental regulation restrictions, the current manufacturing industry is shifting towards more efficient and sustainable systems. This transformation has promoted the identification of energy saving opportunities and the development of new technologies and strategies oriented to improve the energy efficiency of such systems. This paper outlines and discusses most of the research reported during the last decade regarding energy efficiency in manufacturing systems, the current technologies and strategies to improve that efficiency, identifying and remarking those related to the design of management/control strategies. Based on this fact, this paper aims to provide a review of strategies for reducing energy consumption and optimizing the use of resources within a plant into the context of discrete manufacturing. The review performed concerning the current context of manufacturing systems, control systems implemented, and their transformation towards Industry 4.0 might be useful in both the academic and industrial dimension to identify trends and critical points and suggest further research lines.Peer ReviewedPreprin

Technological evolution in machining processes with CNC machines in the context of the concept of Industry 4.0

Dissertação de mestrado em Industrial EngineeringThe work related to the project of this dissertation will consist of an analysis of the technological evolution of the machining processes with CNC (Computer Numerical Control) machines regarding the new concept of Industry 4.0. The concept fits into the current transformation process for the fourth industrial revolution, such as integrated Cyber-Physical Systems (CPS) within the manufacturing processes using the Internet of Things (IoT) in industrial processes. Faced with technological advances, the processes of Industrial Engineering in machining using CNC machines must undergo adaptations, aiming at substantial increases in the operational effectiveness. Thus, an approach will be made to understand how current processes can adapt to the concept under study when analyzing the evolution of the machining tools for CNC machines in the face of new processes. A thorough study will be done to adapt the methodology of Industry 4.0 applying it to the machining processes in CNC Machines. Thereby, a proposal for future applications will be given on the topics studied. The methodology will be based entirely on a documental analysis research strategy. The virtual technology in machining tools is still a subject in development, being one of the main factors to be understood in this dissertation. In this study, it will be possible to analyze the main factors that can influence directly or indirectly the production processes of a factory with CNC machines. It will be explored and studied the types of machining processes for CNC machines and the types of machining tools developed with virtual technology. When we are talking about virtual technology, we are usually addressing the need for software. In CNC machining operations, there is a CAM (Computer Aided Manufacturing) software that performs machining simulations for CNC machines. Thus, a study and analysis of a production system involving a CAM software, a tool with virtual technology and CNC machines will be done to verify how this set can work encompassed and what changes this production model introduces. In the sequence of this study, an idea of a new production system will be proposed, allowing for a better understanding of the possibilities for application of new approaches in the future.O trabalho relacionado ao projeto desta dissertação de mestrado consistirá de uma análise da evolução tecnológica dos processos de usinagem com as máquinas CNC (Comando Numérico Computacional) em relação ao novo conceito da Indústria 4.0. O conceito se enquadra no atual processo de transformação da quarta revolução industrial, com os Sistemas Ciber-Físicos integrados (CPS) dentro dos processos de fabricação que utilizam a Internet das Coisas (IoT) em processos industriais. Diante dos avanços tecnológicos, os processos de Engenharia Industrial em usinagem utilizando máquinas CNC devem sofrer adaptações, visando um aumento substancial na eficácia operacional. Assim, uma abordagem será feita para entender como os processos atuais podem se adaptar ao conceito em estudo, visando também uma análise da evolução das ferramentas de usinagem para máquinas CNC em face de novos processos. Um estudo minucioso será feito para adaptar a metodologia da Indústria 4.0, aplicando-a aos processos de usinagem em máquinas CNC. Com isso, algumas proposta para aplicações futuras serão apresentadas para os tópicos estudados. A metodologia será totalmente baseada em uma estratégia de investigação documental. A tecnologia virtual em ferramentas de usinagem ainda é um assunto em desenvolvimento, sendo um dos principais fatores a serem compreendidos na realização deste trabalho. Neste estudo, será possível analisar os principais fatores que podem influenciar direta ou indiretamente nos processos de produção de uma fábrica com máquinas CNC. Serão explorados e estudados os tipos de processos de usinagem para máquinas CNC e os tipos de ferramentas de usinagem desenvolvidas com tecnologia virtual. Quando abordamos o assunto sobre tecnologia virtual, geralmente estamos a lidar com a necessidade de um software. Nas operações de usinagem CNC, existe um software CAM (Manufatura Assistida por Computador) que realiza simulações de usinagem para máquinas CNC. Assim, um estudo e análise do sistema de produção envolvendo um software CAM, uma ferramenta com tecnologia virtual e máquinas CNC será feito para verificar como este conjunto pode trabalhar englobado e quais as mudanças para esse modelo de produção. Na sequência dessa análise, será proposta uma ideia de um novo sistema de produção, que permite uma melhor compreensão das possibilidades de aplicação no futuro das novas abordagens

Towards a Cyber-Physical Manufacturing Cloud through Operable Digital Twins and Virtual Production Lines

In last decade, the paradigm of Cyber-Physical Systems (CPS) has integrated industrial manufacturing systems with Cloud Computing technologies for Cloud Manufacturing. Up to 2015, there were many CPS-based manufacturing systems that collected real-time machining data to perform remote monitoring, prognostics and health management, and predictive maintenance. However, these CPS-integrated and network ready machines were not directly connected to the elements of Cloud Manufacturing and required human-in-the-loop. Addressing this gap, we introduced a new paradigm of Cyber-Physical Manufacturing Cloud (CPMC) that bridges a gap between physical machines and virtual space in 2017. CPMC virtualizes machine tools in cloud through web services for direct monitoring and operations through Internet. Fundamentally, CPMC differs with contemporary modern manufacturing paradigms. For instance, CPMC virtualizes machining tools in cloud using remote services and establish direct Internet-based communication, which is overlooked in existing Cloud Manufacturing systems. Another contemporary, namely cyber-physical production systems enable networked access to machining tools. Nevertheless, CPMC virtualizes manufacturing resources in cloud and monitor and operate them over the Internet. This dissertation defines the fundamental concepts of CPMC and expands its horizon in different aspects of cloud-based virtual manufacturing such as Digital Twins and Virtual Production Lines. Digital Twin (DT) is another evolving concept since 2002 that creates as-is replicas of machining tools in cyber space. Up to 2018, many researchers proposed state-of-the-art DTs, which only focused on monitoring production lifecycle management through simulations and data driven analytics. But they overlooked executing manufacturing processes through DTs from virtual space. This dissertation identifies that DTs can be made more productive if they engage directly in direct execution of manufacturing operations besides monitoring. Towards this novel approach, this dissertation proposes a new operable DT model of CPMC that inherits the features of direct monitoring and operations from cloud. This research envisages and opens the door for future manufacturing systems where resources are developed as cloud-based DTs for remote and distributed manufacturing. Proposed concepts and visions of DTs have spawned the following fundamental researches. This dissertation proposes a novel concept of DT based Virtual Production Lines (VPL) in CPMC in 2019. It presents a design of a service-oriented architecture of DTs that virtualizes physical manufacturing resources in CPMC. Proposed DT architecture offers a more compact and integral service-oriented virtual representations of manufacturing resources. To re-configure a VPL, one requirement is to establish DT-to-DT collaborations in manufacturing clouds, which replicates to concurrent resource-to-resource collaborations in shop floors. Satisfying the above requirements, this research designs a novel framework to easily re-configure, monitor and operate VPLs using DTs of CPMC. CPMC publishes individual web services for machining tools, which is a traditional approach in the domain of service computing. But this approach overcrowds service registry databases. This dissertation introduces a novel fundamental service publication and discovery approach in 2020, OpenDT, which publishes DTs with collections of services. Experimental results show easier discovery and remote access of DTs while re-configuring VPLs. Proposed researches in this dissertation have received numerous citations both from industry and academia, clearly proving impacts of research contributions

Science Hackathons for Cyberphysical System Security Research: Putting CPS testbed platforms to good use

A challenge is to develop cyber-physical system scenarios that reflect the diversity and complexity of real-life cyber-physical systems in the research questions that they address. Time-bounded collaborative events, such as hackathons, jams and sprints, are increasingly used as a means of bringing groups of individuals together, in order to explore challenges and develop solutions. This paper describes our experiences, using a science hackathon to bring individual researchers together, in order to develop a common use-case implemented on a shared CPS testbed platform that embodies the diversity in their own security research questions. A qualitative study of the event was conducted, in order to evaluate the success of the process, with a view to improving future similar events

Industry 4.0—from Smart Factory to Cognitive Cyberphysical Production System and Cloud Manufacturing

This book focuses on recent developments in new industrial platforms, with Industry 4.0 on its way to becoming Industry 5.0. The book covers smart decision support systems for green and sustainable machining, microscale machining, cyber-physical production networks, and the optimization of assembly lines. The modern multiobjective algorithms and multicriteria decision-making methods are applied to various real-world industrial problems. The emerging problem of cybersecurity in advanced technologies is addressed as well

Cyber-Physical Manufacturing Metrology Model (CPM3) - Big Data Analytics Issue

Internet of Things (IoT) is changing the world, and therefore the application of ICT (Information and Communication Technology) in manufacturing. As a paradigm based on the Internet, IoT utilizes the benefits of interrelated technologies/smart devices such as RFID (Radio Frequency Identification) and WSAN (Wireless Sensor and Actuator Networks) for the retrieval and exchange of information thus opening up new possibilities for integration of manufacturing system and its cyber representation through Cyber-Physical Manufacturing (CPM) model. On the other hand, CPM and digital manufacturing represent the key elements for implementation of Industry 4.0 and backbone for "smart factory" generation. Interconnected smart devices generate huge databases (big data), so that Cloud computing becomes indispensable tool to support the CPM. In addition, CPM has an extremely expressed requirement for better control, monitoring and data management. Limitations still exist in storages, networks and computers, as well as in the tools for complex data analysis, detection of its structure and retrieval of useful information. Products, resources, and processes within smart factory are realized and controlled through CPM model. In this context, our recent research efforts in the field of quality control and manufacturing metrology are directed to the development of framework for Cyber-Physical Manufacturing Metrology Model (CPM3). CPM3 framework will be based on: 1) integration of digital product metrology information obtained from big data using BDA (big data analytics) through metrology features recognition, and 2) generation of global/local inspection plan for CMM (Coordinate Measuring Machine) from extracted information. This paper will present recent results of our research on CPM3 - big data analytics issue

An intelligent real-time cyber-physical toolset for energy and process prediction and optimisation in the future industrial Internet of Things

Energy waste significantly contributes to increased costs in the automotive manufacturing industry, which is subject to energy usage restrictions and taxation from national and international policy makers and restrictions and charges from national energy providers. For example, the UK Climate Change Levy, charged to businesses at 0.554p/kWh equates to 7.28% of a manufacturing business’s energy bill based on an average total usage rate of 7.61p/kWh. Internet of Things (IoT) energy monitoring systems are being developed, however, there has been limited consideration of services for efficient energy-use and minimisation of production costs in industry. This paper presents the design, development and validation of a novel, adaptive Cyber-Physical Toolset to optimise cumulative plant energy consumption through characterisation and prediction of the active and reactive power of three-phase industrial machine processes. Extensive validation has been conducted in automotive manufacture production lines with industrial three-phase Hurco VM1 computer numerical control (CNC) machines