A cyber-physical machine tools platform using OPC UA and MTConnect

Cyber-Physical Machine Tools (CPMT) represent a new generation of machine tools that are smarter, well connected, widely accessible, more adaptive and more autonomous. Development of CPMT requires standardized information modelling method and communication protocols for machine tools. This paper proposes a CPMT Platform based on OPC UA and MTConnect that enables standardized, interoperable and efficient data communication among machine tools and various types of software applications. First, a development method for OPC UA-based CPMT is proposed based on a generic OPC UA information model for CNC machine tools. Second, to address the issue of interoperability between OPC UA and MTConnect, an MTConnect to OPC UA interface is developed to transform MTConnect information model and its data to their OPC UA counterparts. An OPC UA-based CPMT prototype is developed and further integrated with a previously developed MTConnect-based CPMT to establish a common CPMT Platform. Third, different applications are developed to demonstrate the advantages of the proposed CPMT Platform, including an OPC UA Client, an advanced AR-assisted wearable Human-Machine Interface and a conceptual framework for CPMT powered cloud manufacturing environment. Experimental results have proven that the proposed CPMT Platform can significantly improve the overall production efficiency and effectiveness in the shop floor

Pembangunan Modul Pengajaran Kendiri (MPK) keusahawanan dalam topik isu keusahawanan bagi pelajar diploma di politeknik

Terdapat pelbagai kaedah pembelajaran yang telah diperkenalkan termasuklah kaedah pembelajaran yang menggunakan pendekatan pembelajaran bermodul secara kendiri. Kajian ini adalah bertujuan untuk mengkaji kesesuaian Modul Pengajaran Kendiri Keusahawanan dalam topik Isu Keusahawanan yang telah dihasilkan bagi pelajar yang mengikuti pengajian Diploma di Jabatan Perdagangan Politeknik. Antara aspek yang dikaji ialah untuk menilai sama ada rekabentuk modul yang dihasilkan dapat memenuhi ciri-ciri modul yang baik, MPK yang dihasilkan dapat membantu mencapai objektif pembelajaran, MPK ini bersifat mesra pengguna dan MPK yang dihasilkan membantu pensyarah menyampaikan pengajarannya dengan lebih berkesan. Kajian ini dilakukan ke atas 110 orang pelajar semester en am yang mengikuti pengajian diploma dan 4 orang pensyarah yang mengajar subjek Keusahawanan di Jabatan Perdagangan Politeknik Sultan Salahuddin Abdul Aziz Shah, Selangor. Kaedah analisa data yang digunakan dalam kajian ini ialah skor min dan peratus. Hasil daripada kajian ini menunjukkan bahawa rekabentuk modul yang dihasilkan memenuhi ciri-ciri modul yang baik, MPK ini membantu untuk mencapai objektif pembelajaran, MPK ini bersifat mesra pengguna dan MPK yang dihasilkan dapat membantu pensyarah menyampaikan pengajarannya dengan lebih berkesan. Ini bermakna secara keseluruhannya, hasil kajian menunjukkan bahawa modul yang dihasilkan oleh pengkaji adalah sesuai digunakan oleh pelajar-pelajar semester enam yang mengikuti pengajian diploma di Jabatan Perdagangan peringkat politeknik. Seterusnya, beberapa pandangan telah dikemukakan bagi meningkatkan rnutu dan kualiti MPK yang dihasilkan. Semoga kajian ini dapat memberi manfaat kepada mereka yang terlibat dalam bidang pendidikan

Analysis and evaluation of multi-agent systems for digital production planning and control

Industrial manufacturing companies have different IT control functions that can be represented with a so-called hierarchical automation pyramid. While these conventional software systems especially support the mass production with consistent demand, the future project “Industry 4.0” focuses on customer-oriented and adaptable production processes. In order to move from conventional production systems to a factory of the future, the control levels must be redistributed. With the help of cyber-physical production systems, an interoperable architecture must be, implemented which removes the hierarchical connection of the former control levels. The accompanied digitalisation of industrial companies makes the transition to modular production possible. At the same time, the requirements for production planning and control are increasing, which can be solved with approaches such as multi-agent systems (MASs). These software solutions are autonomous and intelligent objects with a distinct collaborative ability. There are different modelling methods, communication and interaction structures, as well as different development frameworks for these new systems. Since multi-agent systems have not yet been established as an industrial standard due to their high complexity, they are usually only tested in simulations. In this bachelor thesis, a detailed literature review on the topic of MASs in the field of production planning and control is presented. In addition, selected multi-agent approaches are evaluated and compared using specific classification criteria. In addition, the applicability of using these systems in digital and modular production is assessed

Integration of Cutting-Edge Interoperability Approaches in Cyber-Physical Production Systems and Industry 4.0

Interoperability in smart manufacturing refers to how interconnected cyber-physical components exchange information and interact. This is still an exploratory topic, and despite the increasing number of applications, many challenges remain open. This chapter presents an integrative framework to understand common practices, concepts, and technologies used in trending research to achieve interoperability in production systems. The chapter starts with the question of what interoperability is and provides an alternative answer based on influential works in the field, followed by the presentation of important reference mod4els and their relation to smart manufacturing. It continues by discussing different types of interoperability, data formats, and common ontologies necessary for the integration of heterogeneous systems and the contribution of emerging technologies in achieving interoperability. This chapter ends with a discussion of a recent use case and final remarks

Applications integration for manufacturing control systems with particular reference to software interoperability issues

The introduction and adoption of contemporary computer aided manufacturing control systems (MCS) can help rationalise and improve the productivity of manufacturing related activities. Such activities include product design, process planning and production management with CAD, CAPP and CAPM. However, they tend to be domain specific and would generally have been designed as stand-alone systems where there is a serious lack of consideration for integration requirements with other manufacturing activities outside the area of immediate concern. As a result, "islands of computerisation" exist which exhibit deficiencies and constraints that inhibit or complicate subsequent interoperation among typical MCS components. As a result of these interoperability constraints, contemporary forms of MCS typically yield sub-optimal benefits and do not promote synergy on an enterprise-wide basis. The move towards more integrated manufacturing systems, which requires advances in software interoperability, is becoming a strategic issue. Here the primary aim is to realise greater functional synergy between software components which span engineering, production and management activities and systems. Hence information of global interest needs to be shared across conventional functional boundaries between enterprise functions. The main thrust of this research study is to derive a new generation of MCS in which software components can "functionally interact" and share common information through accessing distributed data repositories in an efficient, highly flexible and standardised manner. It addresses problems of information fragmentation and the lack of formalism, as well as issues relating to flexibly structuring interactions between threads of functionality embedded within the various components. The emphasis is on the: • definition of generic information models which underpin the sharing of common data among production planning, product design, finite capacity scheduling and cell control systems. • development of an effective framework to manage functional interaction between MCS components, thereby coordinating their combined activities. • "soft" or flexible integration of the MCS activities over an integrating infrastructure in order to (i) help simplify typical integration problems found when using contemporary interconnection methods for applications integration; and (ii) enable their reconfiguration and incremental development. In order to facilitate adaptability in response to changing needs, these systems must also be engineered to enable reconfigurability over their life cycle. Thus within the scope of this research study a new methodology and software toolset have been developed to formally structure and support implementation, run-time and change processes. The tool set combines the use of IDEFO (for activity based or functional modelling), IDEFIX (for entity-attribute relationship modelling), and EXPRESS (for information modelling). This research includes a pragmatic but effective means of dealing with legacyl software, which often may be a vital source of readily available information which supports the operation of the manufacturing enterprise. The pragmatism and medium term relevance of the research study has promoted particular interest and collaboration from software manufacturers and industrial practitioners. Proof of concept studies have been carried out to implement and evaluate the developed mechanisms and software toolset

An End-to-End Big Data Analytics Platform for IoT-enabled Smart Factories: A Case Study of Battery Module Assembly System for Electric Vehicles

Within the concept of factories of the future, big data analytics systems play a critical role in supporting decision-making at various stages across enterprise processes. However, the design and deployment of industry-ready, lightweight, modular, flexible, and low-cost big data analytics solutions remains one of the main challenges towards the Industry 4.0 enabled digital transformation. This paper presents an end-to-end IoT-based big data analytics platform that consists of five interconnected layers and several components for data acquisition, integration, storage, analytics and visualisation purposes. The platform architecture benefits from state-of-the-art technologies and integrates them in a systematic and interoperable way with clear information flows. The developed platform has been deployed in an Electric Vehicle (EV) battery module smart assembly automation system designed by the Automation Systems Group (ASG) at the University of Warwick, UK. The developed proof-of-concept solution demonstrates how a wide variety of tools and methods can be orchestrated to work together aiming to support decision-making and to improve both process and product qualities in smart manufacturing environments

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

Agent-based real-time assembly line management for wireless job shop environment

Recent developments in wireless technologies have created opportunities for developing next-generation manufacturing systems with real-time traceability, visibility and interoperability in shop floor planning, execution and control. This paper discusses how to deploy wireless and intelligent technologies to convert physical objects in manufacturing systems into smart objects to introduce and improve the interoperability and visibility between them and thus with manufacturing decision support systems. A reference architecture for wireless manufacturing (WM) is proposed where three types of smart objects are identified. At the same time, the concept of smart object agent (SOA) is presented and the corresponding framework of smart objects management system (SOMS) is constructed. Under this framework and the concept of SOA, a SOA-based WM environment is studied and demonstrated using a near real-life simplified product assembly line for the collection and synchronization of the real-time field data from manufacturing workshops. © 2010 IEEE.published_or_final_versionThe IEEE International Conference on Mechatronics and Automation (ICMA) 2010, Xi'an, China, 4-7 August 2010. In Proceedings of the IEEE International Conference on Mechatronics and Automation, 2010, p. 2013-201

Interoperability for Industrial Internet of Things Based on Service-oriented Architecture

The new Industry 4.0 envisions a future for agile and effective integration of the physical operational technologies (OT) and the cyber information technologies (IT) as well as autonomous cooperation among them. However, the wide variety and heterogeneity of industrial systems and field devices -especially on the factory floor - increase integration complexity. To address these challenges, new technologies and concepts such as the Industrial Internet of Things (IIoT), Service-oriented Architecture (SoA), Semantic Technologies, Machine Learning and Artificial Intelligence are being introduced to the industrial environment. In this paper, we focus on how industrial automation systems and field devices can be integrated into the IIoT framework and coordinated to adapt to dynamic operating environment. Specifically, this paper proposed an interoperability solution that makes use of SoA and Semantic Technologies to achieve supervised coordination of IIoT application systems. To illustrate the potential of this approach, the Service-oriented Architecture-based Arrowhead Framework is used as the fundamental framework for the implementation of the approach.acceptedVersio