Enhanced integrated modelling approach to reconfiguring manufacturing enterprises

Dynamism and uncertainty are real challenges for present day manufacturing enterprises (MEs). Reasons include: an increasing demand for customisation, reduced time to market, shortened product life cycles and globalisation. MEs can reduce competitive pressure by becoming reconfigurable and change-capable. However, modern manufacturing philosophies, including agile and lean, must complement the application of reconfigurable manufacturing paradigms. Choosing and applying the best philosophies and techniques is very difficult as most MEs deploy complex and unique configurations of processes and resource systems, and seek economies of scope and scale in respect of changing and distinctive product flows. It follows that systematic methods of achieving model driven reconfiguration and interoperation of component based manufacturing systems are required to design, engineer and change future MEs. This thesis, titled Enhanced Integrated Modelling Approach to Reconfiguring Manufacturing Enterprises , introduces the development and prototyping a model-driven environment for the design, engineering, optimisation and control of the reconfiguration of MEs with an embedded capability to handle various types of change. The thesis describes a novel systematic approach, namely enhanced integrated modelling approach (EIMA), in which coherent sets of integrated models are created that facilitates the engineering of MEs especially their production planning and control (PPC) systems. The developed environment supports the engineering of common types of strategic, tactical and operational processes found in many MEs. The EIMA is centred on the ISO standardised CIMOSA process modelling approach. Early study led to the development of simulation models during which various CIMOSA shortcomings were observed, especially in its support for aspects of ME dynamism. A need was raised to structure and create semantically enriched models hence forming an enhanced integrated modelling environment. The thesis also presents three industrial case examples: (1) Ford Motor Company; (2) Bradgate Furniture Manufacturing Company; and (3) ACM Bearings Company. In order to understand the system prior to realisation of any PPC strategy, multiple process segments of any target organisation need to be modelled. Coherent multi-perspective case study models are presented that have facilitated process reengineering and associated resource system configuration. Such models have a capability to enable PPC decision making processes in support of the reconfiguration of MEs. During these case studies, capabilities of a number of software tools were exploited such as Arena®, Simul8®, Plant Simulation®, MS Visio®, and MS Excel®. Case study results demonstrated effectiveness of the concepts related to the EIMA. The research has resulted in new contributions to knowledge in terms of new understandings, concepts and methods in following ways: (1) a structured model driven integrated approach to the design, optimisation and control of future reconfiguration of MEs. The EIMA is an enriched and generic process modelling approach with capability to represent both static and dynamic aspects of an ME; and (2) example application cases showing benefits in terms of reduction in lead time, cost and resource load and in terms of improved responsiveness of processes and resource systems with a special focus on PPC; (3) identification and industrial application of a new key performance indicator (KPI) known as P3C the measuring and monitoring of which can aid in enhancing reconfigurability and responsiveness of MEs; and (4) an enriched modelling concept framework (E-MUNE) to capture requirements of static and dynamic aspects of MEs where the conceptual framework has the capability to be extended and modified according to the requirements. The thesis outlines key areas outlining a need for future research into integrated modelling approaches, interoperation and updating mechanisms of partial models in support of the reconfiguration of MEs

The contribution of industry 4.0 technologies to increase internal and external operational flexibility of production systems

Manufacturing flexibility is recognized as an essential competitive factor in the company's operational strategy as a response to market uncertainties and turbulence. Industry 4.0 emerges as a new industrial paradigm that allows meeting these types of needs of manufacturing companies, focusing on the creation of an intelligent system along the entire value chain that allows the achievement of flexible and adaptive processes. However, the academic literature has not yet presented empirical evidence on how each specific Industry 4.0 technology can contribute to operational flexibility requirements. Although Industry 4.0 is treated as a solution to this need, it is known that there are different types of implementations of Industry 4.0 depending on the operational objectives pursued and the characteristics of the companies. Therefore, the technological sets of Industry 4.0 can have different forms of contribution to achieve greater flexibility in production processes. The aim of this thesis is to create a framework to help companies implement flexible operations in the context of Industry 4.0. The study followed a mixed approach, combining qualitative and quantitative methods. In quantitative terms, the thesis presents two survey research. The first was conducted with 94 companies in the machinery and equipment sector, through which the effect that different operational objectives – including flexibility – have on the definition of technological arrangements in Industry 4.0, is analyzed. The second was conducted with 379 companies, with the objective of analyzing how the smart supply chain concept contributes to the flexibility of the supply chain, especially in the context of uncertainties.. On the other hand, in qualitative terms, the thesis presents a multi-case study in 11 leading manufacturing companies in the implementation of 4.0 technologies, aiming to understand how these technologies are implemented to achieve different operational flexibility requirements. The present thesis demonstrates that, in fact, 4.0 technologies contribute to operational flexibility, but also explores the limitations and nuances of these contributions in different situations. The main contribution of this study is to provide empirical evidence of the effectiveness of different technologies used in a combined way to increase operational flexibility at its different levels.A flexibilidade da manufatura é reconhecida como um fator competitivo essencial na estratégia operacional das empresas, como resposta a necessidades do mercado, especialmente diante de incertezas e turbulências. A Industria 4.0 surge como um novo paradigma industrial que permite atender esse tipo de necessidades das empresas manufatureiras, sendo seu foco a criação de um sistema inteligente ao longo de toda a cadeia de valor que possibilita a obtenção de processos flexíveis e adaptativos. Contudo, a literatura acadêmica ainda não tem apresentado evidências empíricas sobre a forma como cada tecnologia específica da Indústria 4.0 pode contribuir para os requisitos de flexibilidade operacional. Embora Industria 4.0 seja apresentada como uma solução para essa necessidade, é sabido que existem diferentes tipos de implementação da Indústria 4.0 que dependem dos objetivos operacionais almejados e das características das empresas. Portanto, os conjuntos tecnológicos da Indústria 4.0 podem ter diferentes formas de contribuição para alcançar uma maior flexibilidade dos processos de produção. O objetivo desta tese é criar um framework para auxiliar as empresas na implementação de operações flexíveis no contexto da Indústria 4.0. O estudo seguiu uma abordagem mista, combinando métodos qualitativos e quantitativo. Em termos quantitativos, a tese apresenta duas pesquisas survey. A primeira foi conduzida com 94 empresas do setor de máquinas e equipamentos, através da qual se analisa o efeito que diferentes objetivos operacionais dentre eles a flexibilidade possuem sobre a definição de arranjos tecnológicos da Indústria 4.0. A segunda foi conduzida com 379 empresas, com objetivo de analisar como o conceito de smart supply chain contribui para a flexibilidade da cadeia de suprimento, principalmente no contexto de incertezas. Por outro lado, em termos qualitativos, a tese apresenta um estudo multicasos em 11 empresas de manufatura líderes na implantação de tecnologias 4.0, visando entender a forma como essas tecnologias são implementadas para alcançar diferentes requisitos de flexibilidade operacional. A presente tese demonstra que, de fato, as tecnologias 4.0 contribuem para a flexibilidade operacional, mas também explora as limitações e nuances dessas contribuições em diferentes situações. A principal contribuição deste estudo é fornecer evidências empíricas da efetividade de diferentes tecnologias utilizadas de forma combinada para incrementar a flexibilidade operacional nos seus diferentes níveis

Performance measurement on automotive assembly line

Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores (Automação). Universidade do Porto. Faculdade de Engenharia. 201

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.

A Modeling and Analysis Framework To Support Monitoring, Assessment, and Control of Manufacturing Systems Using Hybrid Models

The manufacturing industry has constantly been challenged to improve productivity, adapt to continuous changes in demand, and reduce cost. The need for a competitive advantage has motivated research for new modeling and control strategies able to support reconfiguration considering the coupling between different aspects of plant floor operations. However, models of manufacturing systems usually capture the process flow and machine capabilities while neglecting the machine dynamics. The disjoint analysis of system-level interactions and machine-level dynamics limits the effectiveness of performance assessment and control strategies. This dissertation addresses the enhancement of productivity and adaptability of manufacturing systems by monitoring and controlling both the behavior of independent machines and their interactions. A novel control framework is introduced to support performance monitoring and decision making using real-time simulation, anomaly detection, and multi-objective optimization. The intellectual merit of this dissertation lies in (1) the development a mathematical framework to create hybrid models of both machines and systems capable of running in real-time, (2) the algorithms to improve anomaly detection and diagnosis using context-sensitive adaptive threshold limits combined with context-specific classification models, and (3) the construction of a simulation-based optimization strategy to support decision making considering the inherent trade-offs between productivity, quality, reliability, and energy usage. The result is a framework that transforms the state-of-the-art of manufacturing by enabling real-time performance monitoring, assessment, and control of plant floor operations. The control strategy aims to improve the productivity and sustainability of manufacturing systems using multi-objective optimization. The outcomes of this dissertation were implemented in an experimental testbed. Results demonstrate the potential to support maintenance actions, productivity analysis, and decision making in manufacturing systems. Furthermore, the proposed framework lays the foundation for a seamless integration of real systems and virtual models. The broader impact of this dissertation is the advancement of manufacturing science that is crucial to support economic growth. The implementation of the framework proposed in this dissertation can result in higher productivity, lower downtime, and energy savings. Although the project focuses on discrete manufacturing with a flow shop configuration, the control framework, modeling strategy, and optimization approach can be translated to job shop configurations or batch processes. Moreover, the algorithms and infrastructure implemented in the testbed at the University of Michigan can be integrated into automation and control products for wide availability.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147657/1/migsae_1.pd

Flexible Automation and Intelligent Manufacturing: The Human-Data-Technology Nexus

This is an open access book. It gathers the first volume of the proceedings of the 31st edition of the International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2022, held on June 19 – 23, 2022, in Detroit, Michigan, USA. Covering four thematic areas including Manufacturing Processes, Machine Tools, Manufacturing Systems, and Enabling Technologies, it reports on advanced manufacturing processes, and innovative materials for 3D printing, applications of machine learning, artificial intelligence and mixed reality in various production sectors, as well as important issues in human-robot collaboration, including methods for improving safety. Contributions also cover strategies to improve quality control, supply chain management and training in the manufacturing industry, and methods supporting circular supply chain and sustainable manufacturing. All in all, this book provides academicians, engineers and professionals with extensive information on both scientific and industrial advances in the converging fields of manufacturing, production, and automation

Web service control of component-based agile manufacturing systems

Current global business competition has resulted in significant challenges for manufacturing and production sectors focused on shorter product lifecyc1es, more diverse and customized products as well as cost pressures from competitors and customers. To remain competitive, manufacturers, particularly in automotive industry, require the next generation of manufacturing paradigms supporting flexible and reconfigurable production systems that allow quick system changeovers for various types of products. In addition, closer integration of shop floor and business systems is required as indicated by the research efforts in investigating "Agile and Collaborative Manufacturing Systems" in supporting the production unit throughout the manufacturing lifecycles. The integration of a business enterprise with its shop-floor and lifecycle supply partners is currently only achieved through complex proprietary solutions due to differences in technology, particularly between automation and business systems. The situation is further complicated by the diverse types of automation control devices employed. Recently, the emerging technology of Service Oriented Architecture's (SOA's) and Web Services (WS) has been demonstrated and proved successful in linking business applications. The adoption of this Web Services approach at the automation level, that would enable a seamless integration of business enterprise and a shop-floor system, is an active research topic within the automotive domain. If successful, reconfigurable automation systems formed by a network of collaborative autonomous and open control platform in distributed, loosely coupled manufacturing environment can be realized through a unifying platform of WS interfaces for devices communication. The adoption of SOA- Web Services on embedded automation devices can be achieved employing Device Profile for Web Services (DPWS) protocols which encapsulate device control functionality as provided services (e.g. device I/O operation, device state notification, device discovery) and business application interfaces into physical control components of machining automation. This novel approach supports the possibility of integrating pervasive enterprise applications through unifying Web Services interfaces and neutral Simple Object Access Protocol (SOAP) message communication between control systems and business applications over standard Ethernet-Local Area Networks (LAN's). In addition, the re-configurability of the automation system is enhanced via the utilisation of Web Services throughout an automated control, build, installation, test, maintenance and reuse system lifecycle via device self-discovery provided by the DPWS protocol...cont'd