CHANGE-READY MPC SYSTEMS AND PROGRESSIVE MODELING: VISION, PRINCIPLES, AND APPLICATIONS

The last couple of decades have witnessed a level of fast-paced development of new ideas, products, manufacturing technologies, manufacturing practices, customer expectations, knowledge transition, and civilization movements, as it has never before. In today\u27s manufacturing world, change became an intrinsic characteristic that is addressed everywhere. How to deal with change, how to manage it, how to bind to it, how to steer it, and how to create a value out of it, were the key drivers that brought this research to existence. Change-Ready Manufacturing Planning and Control (CMPC) systems are presented as the first answer. CMPC characteristics, change drivers, and some principles of Component-Based Software Engineering (CBSE) are interwoven to present a blueprint of a new framework and mind-set in the manufacturing planning and control field, CMPC systems. In order to step further and make the internals of CMPC systems/components change-ready, an enabling modeling approach was needed. Progressive Modeling (PM), a forward-looking multi-disciplinary modeling approach, is developed in order to modernize the modeling process of today\u27s complex industrial problems and create pragmatic solutions for them. It is designed to be pragmatic, highly sophisticated, and revolves around many seminal principles that either innovated or imported from many disciplines: Systems Analysis and Design, Software Engineering, Advanced Optimization Algorisms, Business Concepts, Manufacturing Strategies, Operations Management, and others. Problems are systemized, analyzed, componentized; their logic and their solution approaches are redefined to make them progressive (ready to change, adapt, and develop further). Many innovations have been developed in order to enrich the modeling process and make it a well-assorted toolkit able to address today\u27s tougher, larger, and more complex industrial problems. PM brings so many novel gadgets in its toolbox: function templates, advanced notation, cascaded mathematical models, mathematical statements, society of decision structures, couplers--just to name a few. In this research, PM has been applied to three different applications: a couple of variants of Aggregate Production Planning (APP) Problem and the novel Reconfiguration and Operations Planning (ROP) problem. The latest is pioneering in both the Reconfigurable Manufacturing and the Operations Management fields. All the developed models, algorithms, and results reveal that the new analytical and computational power gained by PM development and demonstrate its ability to create a new generation of unmatched large scale and scope system problems and their integrated solutions. PM has the potential to be instrumental toolkit in the development of Reconfigurable Manufacturing Systems. In terms of other potential applications domain, PM is about to spark a new paradigm in addressing large-scale system problems of many engineering and scientific fields in a highly pragmatic way without losing the scientific rigor

RMS capacity utilisation: product family and supply chain

yesThe paper contributes to development of RMS through linkage with external stakeholders such as customers and suppliers of parts/raw materials to handle demand fluctuations that necessitate information sharing across the supply chain tiers. RMS is developed as an integrated supply chain hub for adjusting production capacity using a hybrid methodology of decision trees and Markov analysis. The proposed Markov Chain model contributes to evaluate and monitor system reconfigurations required due to changes of product families with consideration of the product life cycles. The simulation findings indicate that system productivity and financial performance in terms of the profit contribution of product-process allocation will vary over configuration stages. The capacity of an RMS with limited product families and/or limited model variants becomes gradually inoperative whilst approaching upcoming configuration stages due to the end of product life cycles. As a result, reconfiguration preparation is suggested quite before ending life cycle of an existing product in process, for switching from a product family to a new/another product family in the production range, subject to its present demand. The proposed model is illustrated through a simplified case study with given product families and transition probabilities

Capacity management of modular assembly systems

Companies handling large product portfolio often face challenges that stem from market dynamics. Therefore, in production management, efficient planning approaches are required that are able to cope with the variability of the order stream to maintain the desired rate of production. Modular assembly systems offer a flexible approach to react to these changes, however, there is no all-encompassing methodology yet to support long and medium term capacity management of these systems. The paper introduces a novel method for the management of product variety in assembly systems, by applying a new conceptual framework that supports the periodic revision of the capacity allocation and determines the proper system configuration. The framework has a hierarchical structure to support the capacity and production planning of the modular assembly systems both on the long and medium term horizons. On the higher level, a system configuration problem is solved to assign the product families to dedicated, flexible or reconfigurable resources, considering the uncertainty of the demand volumes. The lower level in the hierarchy ensures the cost optimal production planning of the system by optimizing the lot sizes as well as the required number of resources. The efficiency of the proposed methodology is demonstrated through the results of an industrial case study from the automotive sector. © 2017 The Society of Manufacturing Engineer

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

Life Cycle of Multi Technology Machine Tools – Modularization and Integral Design

AbstractFor reasons of high flexibility but still maximum productivity, machine tools integrating various production technologies have recently received particular attention. Combining and integrating multiple manufacturing techniques into one single system in early stages of the product emergence process is challenging. To keep the effort for implementation to a minimum, an initiation already in the concept phase is being actively pursued. Design guidelines are currently investigated based on the examination of different technology combinations.This approach focuses on systematic conceptual design for such hybrid machine technologies. Product architectures are used to describe the modularity and create a specific delimitation for standardization. Reference product architectures for Multi Technology Machine Tools (MTMT) carry high potential for saving expenses in product development. The main emphasis is on technology and system integration. A technological similarity assessment of the single processes involved forms the basis of this approach to assure potential for synergies. Monetary aspects in early stages of product development are considered. Based on the analysis a generic system model is connected with general product architectures for MTMT.The method introduced is validated by a Multi-Technology Machining Centre with two simultaneously usable workspaces integrating a milling spindle and two laser processing units. The research undertaken is part of the Cluster of Excellence “Integrative Production Technology for High-Wage Countries” and has been funded by German Research Foundation (DFG)