Decentralized Robust Capacity Control of Job Shop Systems with Reconfigurable Machine Tools

Manufacturing companies are confronted with various challenges from the perspective of customers individual requirements concerning variations of types of products, quantities and delivery dates. This renders the manufacturing process to be more dynamic and complex, which may result in bottlenecks and unbalanced capacity distributions. To cope with these problems, capacity adjustment is an effective approach to balance capacity and load for short or medium term fluctuations on the operational layer. Particularly, new technologies and algorithms need to be developed for the implementation of capacity adjustment. Reconfigurable machine tools (RMTs) and operator-based robust right coprime factorization (RRCF) provide an opportunity for a new capacity control strategy. Therefore, the main purpose of the research is to develop an effective machinery-oriented capacity control strategy by incorporating RMTs and RRCF for a job shop system to deal with volatile customer demands

Nonlinear Model Predictive Control for Industrial Manufacturing Processes with Reconfigurable Machine Tools

Manufacturing companies are faced with challenges to respond to volatile market demands quickly and flexibly while maintaining a cost-effective level of production. Instead of flexible working times, we adopt Reconfigurable Machine Tools (RMTs) to compensate for unpredictable events in case of bottleneck. To include these tools effectively on the operational layer, we propose a complementing feedback approach using model predictive control (MPC) together with genetic algorithm and branch and bound to achieve a better compliance with logistics objectives and a sustainable demand oriented capacity allocation. Further, the system stability is guaranteed by a trajectory-based unconstrained MPC scheme associated with the principle of flexible Lyapunov functions. The effectiveness and plug-and-play availability of the proposed method is demonstrated via a four-workstation job-shop system, which shows that the work in process can be practically asymptotically stabilized by usage of RMTs

Agent-based Hierarchical Planning and Scheduling Control in Dynamically Integrated Manufacturing System

It has been broadly recognised that today’s manufacturing organisations face increasing pressures from continuous and unexpected changes in the business environment such as changes in product types, changes in demand pattern, changes in manufacturing technologies etc. To enable manufacturing organisations to rapidly and timely deal with these changes, operational decisions (e.g., process planning and production scheduling) have to be integrated with dynamic system restructure or reconfiguration so that manufacturing organisations do not only use the flexible resource utilisations to deal with these changes, but also can dynamically reconfigure their existing system structures in response these changes. A manufacturing system concept and implementation methodology is proposed by the Exeter Manufacturing Enterprise Centre (XMEC), which is called the Dynamically Integrated Manufacturing System (DIMS). The overall aim of DIMS is to provide a systematic modelling and control framework in which operational decisions can be integrated with the dynamic system restructuring decisions so as to help manufacturing systems to dynamically deal with changes in the business environment. This PhD research is a part of DIMS research, which focuses on the investigation on operational control in DIMS. Based on the established agent-based modelling architecture in DIMS, this research develops two agent bidding mechanisms for the hierarchical control of production planning and scheduling. These two mechanisms work together to assist manufacturing systems in making optimal and flexible operational decisions in response to changes in the business environment. The first mechanism is the iterative agent bidding mechanism based on a Genetic Algorithm (GA) which facilitates the determination of the optimal or near optimal allocation of a production job containing a set of sub-jobs to a pool of heterarchical resources. The second mechanism is the hierarchical agent bidding mechanism which enables product orders to be cost-efficiently and flexibly planned and scheduled to meet the orders’ due dates. The novelty of this mechanism is that it enables orders to be fulfilled within structural constraints of manufacturing systems as far as possible and however enables resources to be regrouped flexibly across system boundaries when orders cannot be fulfilled within structural constraints of manufacturing systems

Feasibility analysis of using special purpose machines for drilling-related operations

This work focuses on special purpose machine tools (SPMs), providing a modular platform for performing drilling-related operations. One of the main challenges in using SPMs is selecting the most appropriate machine tool among many alternatives. This thesis introduces a feasibility analysis procedure developed to support decision-making through the assessment of the strengths and limitations of SPMs. To achieve this, technical and economic feasibility analyses, a sensitivity analysis, and an optimisation model were developed and a case study was provided for each analysis. The results indicated that although technical feasibility analysis leads decision-makers to select a feasible machine tool, complementary analyses are required for making an informed decision and improving profitability. Accordingly, a mathematical cost model was developed to perform economic and sensitivity analyses and investigate the profitability of any selected SPM configuration. In addition, an optimisation procedure was applied to the cost model in order to investigate the effect of process parameters and the SPM configuration on the decision-making. Finally, the developed analyses were then integrated into a model in a proper sequence that can evaluate whether the SPM is appropriate for producing the given part and achieving higher productivity. To validate this integrated model three different case studies were presented and results were discussed. The results showed that the developed model is a very useful tool in assisting manufacturers to evaluate the performance of SPMs in comparison with other alternatives considered from different perspectives

Towards practical guidelines for conversion from a fixed to a reconfigurable manufacturing automation system

It is generally considered to be a key requirement in the development of reconfigurable manufacturing systems, that economic feasibility is only attainable if the system is defined to be reconfigurable at the outset of its design. In this work we consider the potential exception to this requirement, in the context of a common industrial scenario where a specialized and expensive manufacturing machine or system will otherwise be rendered useless due to loss of business of the particular product being manufactured. Specific guidelines to convert from a fixed to a reconfigurable system are proposed, and evaluated through a case study.peer-reviewe

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

Towards practical guidelines for conversion from fixed to reconfigurable manufacturing automation systems

It is generally considered that economic feasibility of a reconfigurable manufacturing system is only attainable if the system is defined to be reconfigurable at the outset of its design. In this work we consider the potential exception to this perception, in the context of a common industrial scenario where a specialized and expensive manufacturing machine or system will otherwise be rendered useless due to loss of business of the particular product being manufactured. Specific guidelines to convert from a fixed to a reconfigurable system are proposed, and evaluated through a case study. It is shown that under certain conditions, reconfigurable manufacturing systems may be economically feasible even if they are developed through the modification of pre-existing dedicated systems.peer-reviewe

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.