A framework to offer high value manufacturing through self-reconfigurable manufacturing systems

The High Value Manufacturing (HVM) sector is vital for developed countries due to the creation of innovative products with advanced technology that cannot be reproduced at the same cost and time with traditional technology. The main challenge for HVM is to rapidly increase production volume from one-off products to low production volume. This requires highly flexible manufacturing systems that can produce new products at variable production volumes. Current manufacturing systems, classified as dedicated, flexible and reconfigurable systems, are limited to produce one type of product(s), within a production volume range and have fixed layouts of machines. Thus, there is a need for highly flexible systems that can rapidly adjust their production volume according to the production demand (i.e. main HVM challenge). Therefore, a novel manufacturing framework, called INTelligent REconfiguration for a raPID production change (INTREPID), is presented in this thesis. INTREPID consists of a user interface and communications platform, a job allocation system, a globally distributed network of Reconfigurable Manufacturing Centres (RMCs), consisting of interconnected factories, and Self-Reconfigurable Manufacturing Systems (S-RMSs). The highly flexible S-RMS consists of movable machines and Mobile Manufacturing Robots (MMRs). The novelty of the S-RMS is its capability of forming layouts bespoke to the current production needs. The vision of INTREPID is to offer global HVM services through the network of RMCs. The job allocation system determines the best possible RMCs or factories to perform a job by considering the complexity of the production requirements and the status of the available S-RMSs at each factory. The planning of the production with S-RMS is challenging due to its high flexibility. The main example of this flexibility is the possibility to create layouts bespoke to current production needs. Yet, this flexibility involves the challenges of determining allocations and schedules of tasks to robots and machines, positions to manufacture, and routes to reach those positions. In manufacturing systems with fixed layouts, production plans are determined by solving a sequence of problems. However, for the S-RMS, it is proposed to determine production plans with a single problem that covers the scheduling, machine layout and vehicle routing problems simultaneously. This novel problem is called the Scheduling, positions Assigning and Routing problem (SAR) problem. In order to determine the best possible production plan(s) for the S-RMS, it is necessary to use optimisation methods. Dozens of elements, characteristics and assumptions from the constituent problems might be included in the formulation of the SAR problem. Elements, characteristics and assumptions can be considered as decision variables on whether to include or not the elements and characteristics and under which assumptions in the formulation. There are two types of decision variables. Fundamental variables are natural to the SAR problem (e.g. manufacturing resources, factory design and operation), whilst auxiliary variables arise from the aim to simplify the formulation of the optimisation problem (i.e. time formulated as discrete or continuous). Due to the large number of decision variables, there might be millions of possible ways to formulate the SAR problem (i.e. the SAR problem space). Some of these variants are intractable to be solved with optimisation methods. Hence, before formulating the SAR problem, it is necessary to select a problem(s) that is realistic to industrial scenarios but solvable with optimisation methods. Existing selection methods work with pairwise comparisons of alternatives. However, for a space of millions of SAR problems, pairwise comparisons are intractable. Hence, in this thesis, a novel Decision Making Methodology (DMM) based on the controlled convergence method is presented. The DMM helps down-selecting one or a few SAR problems from millions of possible SAR problems. The DMM is demonstrated with a case study of the SAR problem and the results show a significant reduction of the reviewed SAR problems and the time to select them

Agent-based asset administration shell approach for digitizing industrial assets

Modern manufacturing systems are facing new challenges related to the fast-changing market conditions, increased global competition and rapid technological developments, imposing strong requirements in terms of flexibility, robustness and reconfigurability. In this context, the Industry 4.0 (I4.0) paradigm relies on digitizing industrial assets to fulfil these requirements. The implementation of this digitization process is being promoted by the so-called Asset Administration Shell (AAS), a digital representation of an asset that complies with standardization and interoperability strategies. At this moment, a significant part of the AAS developments is more focused on the information management of the asset along its lifecycle and not concerned with aspects of intelligence and collaboration, which are fundamental aspects to develop I4.0 compliant solutions. In this sense, this paper presents an agent-based AAS approach for enhancing the digitization process of assets, considering agents to embed distributed intelligence and collaborative functions, service orientation to support interoperability, and holonic principles to provide the system organization. The proposed agent-based AAS was implemented in an industrial automation system aiming to analyze its applicability.info:eu-repo/semantics/publishedVersio

Programmable photonics : an opportunity for an accessible large-volume PIC ecosystem

We look at the opportunities presented by the new concepts of generic programmable photonic integrated circuits (PIC) to deploy photonics on a larger scale. Programmable PICs consist of waveguide meshes of tunable couplers and phase shifters that can be reconfigured in software to define diverse functions and arbitrary connectivity between the input and output ports. Off-the-shelf programmable PICs can dramatically shorten the development time and deployment costs of new photonic products, as they bypass the design-fabrication cycle of a custom PIC. These chips, which actually consist of an entire technology stack of photonics, electronics packaging and software, can potentially be manufactured cheaper and in larger volumes than application-specific PICs. We look into the technology requirements of these generic programmable PICs and discuss the economy of scale. Finally, we make a qualitative analysis of the possible application spaces where generic programmable PICs can play an enabling role, especially to companies who do not have an in-depth background in PIC technology

Engineering methods and tools for cyber–physical automation systems

Much has been published about potential benefits of the adoption of cyber–physical systems (CPSs) in manufacturing industry. However, less has been said about how such automation systems might be effectively configured and supported through their lifecycles and how application modeling, visualization, and reuse of such systems might be best achieved. It is vitally important to be able to incorporate support for engineering best practice while at the same time exploiting the potential that CPS has to offer in an automation systems setting. This paper considers the industrial context for the engineering of CPS. It reviews engineering approaches that have been proposed or adopted to date including Industry 4.0 and provides examples of engineering methods and tools that are currently available. The paper then focuses on the CPS engineering toolset being developed by the Automation Systems Group (ASG) in the Warwick Manufacturing Group (WMG), University of Warwick, Coventry, U.K. and explains via an industrial case study how such a component-based engineering toolset can support an integrated approach to the virtual and physical engineering of automation systems through their lifecycle via a method that enables multiple vendors' equipment to be effectively integrated and provides support for the specification, validation, and use of such systems across the supply chain, e.g., between end users and system integrators

Changeable Manufacturing on the Network Level

AbstractAgility in the sense of changeability on the manufacturing network level, and here especially the business perspective, has received less attention than the other dimensions of changeability on the lower production levels, as well as in relation to the technological perspective. The present paper aims to enrich the concept of agility in the aforementioned sense, taking strategic management concepts into account that have so far received less attention in relation to changeability. Namely, we consider the concepts of lead factory, capacity pooling and allying, operational flexibility, and the concept of combining products, services and software as fruitful enrichments of the umbrella concept changeability. In so doing, we highlight interdependencies between agility and the analyzed concepts as well as the other changeability dimensions on the lower production level of factories or sites. On this basis, we formulate six hypotheses in consideration of the presented theoretical derivations. Hence, the methodological approach of our research is conceptual and hypothesis generating. Our work is supposed to build the basis for continuative conceptual and empirical research on agility

Factories of the Future

Engineering; Industrial engineering; Production engineerin

Operator interfaces for the lifecycle support of component based automation systems

Current manufacturing automation systems (specifically the powertrain sector) have been facing challenges with constant pressures of globalisation, environmental concerns and ICT (Information and Communication Technology) innovations. These challenges instigate new demands for shorter product lifecycles and require customised products to be manufactured as efficiently as possible. Manufacturing systems must therefore be agile to remain competitive by supporting frequent reconfigurations involving distributed engineering activities. [Continues.

Mass Production Processes

It is always hard to set manufacturing systems to produce large quantities of standardized parts. Controlling these mass production lines needs deep knowledge, hard experience, and the required related tools as well. The use of modern methods and techniques to produce a large quantity of products within productive manufacturing processes provides improvements in manufacturing costs and product quality. In order to serve these purposes, this book aims to reflect on the advanced manufacturing systems of different alloys in production with related components and automation technologies. Additionally, it focuses on mass production processes designed according to Industry 4.0 considering different kinds of quality and improvement works in mass production systems for high productive and sustainable manufacturing. This book may be interesting to researchers, industrial employees, or any other partners who work for better quality manufacturing at any stage of the mass production processes