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2015 | Book

Foundations & Principles of Distributed Manufacturing

Elements of Manufacturing Networks, Cyber-Physical Production Systems and Smart Automation


About this book

The book presents a coherent description of distributed manufacturing, providing a solid base for further research on the subject as well as smart implementations in companies. It provides a guide for those researching and working in a range of fields, such as smart manufacturing, cloud computing, RFID tracking, distributed automation, cyber physical production and global design anywhere, manufacture anywhere solutions. Foundations & Principles of Distributed Manufacturing anticipates future advances in the fields of embedded systems, the Internet of Things and cyber physical systems, outlining how adopting these innovations could rapidly bring about improvements in key performance indicators, which could in turn generate competition pressure by rendering successful business models obsolete. In laying the groundwork for powerful theoretical models, high standards for the homogeneity and soundness of the suggested setups are applied. The book especially elaborates on the upcoming competition in online manufacturing operations and respective control procedures.

By outlining encapsulation and evolving decision-making principles, Foundations & Principles of Distributed Manufacturing fully conceptualizes the view of manufacturing networks as sets of loosely coupled interacting smart factory objects. Moreover, the book provides concrete approaches to a number of future fields, where distributed manufacturing might be applied. Both researchers and professionals will profit from the authors’ broad experience in Distributed Manufacturing and Fractal Enterprise implementations, where they initiated and completed a number of successful research projects: within the global Intelligent Manufacturing Systems (IMS) scheme, within the European Research Area frameworks as well as national contexts, and both in industry and at leading research institutions. This background ensures well-founded theory on one hand and valuable practical results on the other in a fascinating area that is still under intensive research. Readers will acquire essential insights as well as useful guidance for categorizing and specifying extended distributed manufacturing solutions and their professional implementations.

Table of Contents

Chapter 1. Introduction
The general perception of high performance information and communication technology and upcoming smart network devices in many areas of everyday life makes us expect more innovations to come that are directly relevant for manufacturing. The first implementations of cloud solutions and item localisation in manufacturing have provided striking evidence for the power of these devices, and the supposed potential behind is only touched. All these innovations and novelties have groundbreaking and disruptive effects and will therefore jeopardise established business models and even challenge well saturated manufacturing processes’ set ups. The static manufacturing system will definitely be replaced by the dynamic manufacturing network additionally represented by virtualisations of manufacturing units and their connections. Instead of costly suppressing the network nature of manufacturing processes, we may learn to exploit these network properties. Better structured and more formal models are needed for capturing all decisive network features, for guaranteeing software support and for promoting additional standards and tools that will be required for the management. In order to cope with the socio-technical-economical nature of manufacturing, the interdisciplinary base for methodical work has to be consolidated. The book aims at contributing to the addressed fields by proposing a theory framework that captures the new principles and tools that have been identified and established in exhaustive studies on networked manufacturing. Completely new rules of the game with a major shift in skills in the factories and on the shopfloors require more compact descriptions and better theory grounds for the new manufacturing principles that have stepped into the industrial context. For the coherent presentation of the matter, a section structure is motivated and selected audiences for the outline are named.
Hermann Kühnle, Günter Bitsch
Chapter 2. Description of the Working Field
Computing miniaturization, communication networks and smart devices decentralise manufacturing. Various propositions of novel ICT continue to push virtualizations and atomisation of resources, so manufacturing increasingly relies on smart autonomous units enforcing a number of unexpected manufacturing network principles. Hierarchical set ups with command and control structures become outdated; they are replaced by bottom up (self-) configuring versatile networks, as proposed by Distributed Manufacturing. Distributed Manufacturing has impact on a number of manufacturing fundamentals, as the approach is about to generalise distributed automation to manufacturing industry in total. Matching manufacturing fundamentals with the latest ICT achievements irrefutably confirms Cyber Physical Systems (CPS), machine to machine (M2M), RFID and Cloud computing solutions as utmost adequate technology for highly efficient manufacturing processes and cutting edge factory solutions. Especially, real time data and item localisation are changing the game and laying ground for iterative intelligent decision-making and for gradual manufacturing network (re-)configurations. All these developments are additionally flanked by coalescing technology fields, as new materials and nanotechnology, underpinning the dynamics of interdisciplinarity in manufacturing. Smart units in manufacturing are now able to absorb the intelligence, which has been already displayed in distributed industrial automation, for implementations in comprehensive industrial manufacturing contexts. An adequate framework to capture all aspects has to consist of a set of interacting formal models that include both, the real manufacturing objects as well as their virtualisations.
Hermann Kühnle, Günter Bitsch
Chapter 3. Theory Building Approach
The network nature of manufacturing may not be captured by further detailing the systems thinking. The scope has to be widened up. To speed up research progresses, the base for further grounded theory has to be strengthened and the role of outside disciplines for manufacturing has to be newly established in order to profit from the catalysing forces and fruitful impacts of other disciplines’ work. Research work at the intersections of disciplines, changing the core of manufacturing by intensive interaction, necessitates theory building on the base of a unified language. Mathematical topology may be identified as accountable discipline, as it offers adequate abstractions as well as the explicative power to capture the relevant manufacturing contexts and objects. The Hausdorff space with its attached spaces and the respective mappings perfectly translate the Cyber Physical Production Systems into theory and application likewise. Moreover, it smoothly harmonises the relevant models that are applied for effective virtualisations of manufacturing processes, as aimed at. The resulting framework captures all network principles and smart unit properties, and lays ground for standardisation efforts.
Hermann Kühnle, Günter Bitsch
Chapter 4. Core Models, Principles, and Networks’ Structuring
Manufacturing networks fundamentally differ from hierarchical organisations, as they emphasise on speed, re-linking and reconfiguration. For the decisions for realignment of units with reallocations of resources, reconfigurations on varying levels of detail and control actions, generic models represent an adequate description. Units, processes and resources obey specific newly described concurrency principles, with major implications on all manufacturing set ups. Behaviour, parallelism, iteration, encapsulations and emergence will be dominating all virtualizations of resources and objects, perfectly supporting the interrelating manufacturing aspect models for seamless collaboration, also between geographically dispersed resources. Manufacturing objects interact with other manufacturing objects via their respective virtual representations, so, in reality, virtualisations interact with virtualisations. Methods, models and KPI’s appear as embedded items on varying levels of detail supported by fold/unfold mechanisms for the generics, the processes as well as the systems, likewise. Many models in manufacturing management have been built up to harmonise demand and resource availability by taking adequate decisions for assignments and schedules, in many cases by computer programme routines. As all models will also be increasingly used decentralised, the well-known set of manufacturing management models has to be reclassified into the categories of product models, process models and decision support system models for repositioning their network role. Criticality thinking enables levelled continuous decision- and control procedures for manufacturing networks’ structures adaptation and evolution.
Hermann Kühnle, Günter Bitsch
Chapter 5. Smart Manufacturing Units
All enhanced abilities of smart units in manufacturing, especially of machines, product orders and equipment on the shopfloors have to be made available for highly efficient value chains. All objects and items will be in real-time and online. Interactions between virtualisations and models of manufacturing units will appear exactly as interactions with the units themselves. Such newly appearing abilities have decisive impact on the units’ behaviour, the network configurations, the collaboration procedures and the human resource development. The context aware equipment, the autonomous order, the scalable machine capacity or the networkable manufacturing unit will be part of an upcoming professional terminology to get familiar with on the shopfloor as well as for shopfloor management. The most relevant properties in the manufacturing context are exactly described and precisely defined. As all these properties are most important for setting up efficient value chains, their technological readiness and their utmost availability are of high significance. With this aim, all properties are associated with a maturity scale, so the synthesis of all properties may add up to an informative maturity model. This Distributed Manufacturing Maturity Model (D3M) excellently provides for clear positioning and for valuable orientation concerning the technological readiness levels and advances of shop floors, manufacturing areas and factories.  
Hermann Kühnle, Günter Bitsch
Chapter 6. Networking Tools and Information Models—Selected Manufacturing Examples Applying Concurrency Principles and Novel Units’ Properties
Selected Distributed Manufacturing examples from different industry sectors fully verify the theory as well as the principles with the tools. as proposed, and offer valuable sidelines for identifying gaps and obstacles on the way to smart Distributed Manufacturing. All generics, models and instruments may be visualised and configured to describe the case specific context in a catchable way. The outlined cases take deferring approaches to Distributed Manufacturing and to the respective network decisions, as their context and maturity profiles clearly exhibit. Revolving decision cycles are implemented on several levels of detail; on the task level with control loops for tool/material interactions, on the company level as alternative routing options. First experiences with thorough KPI evaluations in pilot areas signalise striking effects that are realised on the base of real time data, smart properties, network principles and hybrid decision procedures, as suggested. Unattended lessons learned as well as a solid outlook onto important managerial implications are given, which the upcoming smart Distributed Manufacturing era is expected to unwrap. The skills of the Digital Native will steadily gain importance: Man-Machine decisions and direct interactions, involving specific decision patterns and advanced bottom-up artificial intelligence, will grow up to decisive production factors. Body area networks and wireless IP connections will give different and non-habitual roles to humans in manufacturing value creation.
Hermann Kühnle, Günter Bitsch
Foundations & Principles of Distributed Manufacturing
Hermann Kühnle
Günter Bitsch
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Electronic ISBN
Print ISBN

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