An optimization approach for predictive-reactive job shop scheduling of reconfigurable manufacturing systems

The manufacturing industry is now moving forward rapidly towards reconfigurability and reliability to meet the hard-topredict global business market, especially job-shop production. However, even if there is a properly planned schedule for production, and there is also a technique for scheduling in Reconfigurable Manufacturing System (RMS) but job-shop production will always come out with errors and disruption due to complex and uncertainty happening during the production process, hence fail to fulfil the due-date requirements. This study proposes a generic control strategy for piloting the implementation of a complex scheduling challenge in an RMS. This study is aimed to formulate an optimization-based algorithm with a simulation tool to reduce the throughput time of complex RMS, which can comply with complex product allocations and flexible routings of the system. The predictive-reactive strategy was investigated, in which Genetic Algorithm (GA) and dispatching rules were used for predictive scheduling and reactivity controls. The results showed that the proposed optimization-based algorithm had successfully reduced the throughput time of the system. In this case, the effectiveness and reliability of RMS are increased by combining the simulation with the optimization algorithm

Optimal Reconfiguration of Complex Production Lines for Profit Maximization via Simulation Modeling

With the recent trend of re-shoring, transferring manufacturing systems from a workforce-intensive to a capital-intensive production environment becomes more common. One challenge multinational manufacturing companies may face in such an endeavor is reconfiguration of the transferred manufacturing system according to the availability of better machinery in the capital-intensive environment. In this dissertation, based on a real-life problem, I develop several simulation optimization methods for the problem of production line reconfiguration. The case is a reverse transfer of manufacturing system/technology, i.e. transfer from a workforce-intensive environment to a capital-intensive one. I investigate the performances of nine different simulation optimization approaches based on the real-life case in automotive industry to illustrate their relative strengths under different parameter scenarios. I also create a test-bed problem to determine the specifications of these methods, and further analyze their performances. Numerical results may guide the practitioners facing similar challenges in choosing a suitable solution approach depending on the problem size and solution time availability

Simulation and optimisation of a specific flexible manufacturing system.

As current market competition evolves, most companies intend to increase their options for product customisation and accelerate their product upgrading. Correspondingly, manufacturers have to face the increasing size of product family, shortened product life cycle or rapid product/process change. Therefore, Flexible Manufacturing Systems (FMS) have been introduced that uses advanced machines and efficient transport systems to produce multiple products at the same time. However, an FMS can be complicated to manage because of the increased variability in products and processes. The research aims to develop manufacturing simulation and optimisation techniques for a FMS. This research will integrate Discrete Event Simulation (DES) and multi-objective optimisation approach to address the complexity and flexibility within an agile manufacturing environment. Due to the complexity of FMS, most current FMS optimisation research has engaged with FMS production problems separately without considering other inter-related problems in the same system such as dealing with operation sequence problem without considering Level of Flexibility (LoF), thus it is hard for the solution to provide a prospective impact for the whole system. There are very few real-world FMS implementations that are available to literatures, making it difficult to build and verify the models within a complete ecosystem. Consequently, most of the models in the research are oversimplified. Therefore, this research aims to develop a method to optimise FMS production considering the overall system, by having access to an FMS industrial implementation. This research contributes to knowledge in four main areas, namely, (1) the interactions of FMS production problems have been investigated, (2) a framework has been developed to integrate the simulation and optimisation for FMS to enable optimisation algorithms working with DES models effectively, (3) a comprehensive FMS simulation model has been built and validated on the industrial shop floor and (4) multi-objective optimisation has been applied to the FMS scheduling problem, considering interactions with other problems. Based on the results and limitations of this research, real-time simulation, mock-up FMS and improve computational efficiency are suggested for future work.PhD in Manufacturin

Dynamic planning and control methodology for large-scale concurrent construction projects

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2001.Includes bibliographical references (leaves 182-185).Concurrent construction has been widely used for modem construction projects, as a method to shorten time-to-market. Concurrent construction, however, requires a careful and systematic approach to its planning and management, since it also has greater potential to impact the construction process than the traditional more serial method. These industrial trends and challenges in concurrent construction, together with increased understanding of dynamics and complexities of construction, have increased the demand for a more efficient planning and control method. In this context, the simulation-based scheduling method that has the potential to more effectively deal with the dynamic state of construction processes has currently emerged as an alternative to the network-based method. However, despite its potential advantages over the network-based method, very few of the existing simulation tools have overcome their practical limitations and have proven their applicability to real construction processes. As an effort to address some of these challenging issues, this thesis presents Dynamic Planning and Control Methodology (DPM) that has been developed to help prepare a more robust construction plan against uncertainties and to provide policy guidelines for the planning and control of a construction project, taking into consideration the context in which the project is being developed. The use of DPM would be especially beneficial for construction projects performed concurrently and involving higher complexity and uncertainties, ensuring that those projects can be delivered in time without driving up costs.by Moonseo Park.Ph.D

A multi-domain process design and improvement framework

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 379-385).Processes in manufacturing, services, and healthcare are complex socio-technical systems composed of intricately sequenced activities supported by elements drawn from multiple domains. While many of these processes offer high performance, their complexity can make their design, improvement, troubleshooting, and change difficult due to the many possible and unforeseen interactions between elements. This thesis develops a design methodology and multi-domain network model for complex process design, change management, process improvement, and troubleshooting. As part of the methodology a feasibility analysis method based on solving the minimum cost flow problem for a network of process alternatives is presented to identify feasible processes subject to stakeholder requirements and constraints including performance, flexibility, modularity, and other system properties. A model based on Multi-Domain Matrix (MDM) concepts is developed specifically for process analysis called the Multi-Domain Process Matrix model (MDPM) to enumerate and analyze the interactions between process elements such that process performance under change and troubleshooting scenarios can be improved. The graph theory basis of the MDPM model enables its analysis using a proposed set of metrics derived from communications, social, and process network literature. As a demonstration of the use of the methodology, a complex DNA sequencing based surveillance process for Methicillin resistant Staphylococcus aureus (MRSA) in the US healthcare system is designed and a prototype implemented. Rapid advances in DNA-based technologies have greatly expanded the range of processes available to the clinical microbiology laboratory, however, integrating these new processes into a comprehensive surveillance system presents significant challenges. Many of these new technologies are still in early stages of development, require multidisciplinary teams to support them, and must undergo significant optimization presenting significant barriers to their rapid adoption despite the pressing need to understand and control antibiotic resistance. Data from the prototype MRSA surveillance process show significant variation at the DNA level between patient cases, providing evidence for the urgent need for a DNA sequencing based microbial surveillance process as part of clinical microbiology efforts in the US healthcare system. However, results of applying the process design methodology and MDPM model analysis indicate significant work remains to reduce complexity, further improve key technology elements, gain acceptance, develop key organizational infrastructure, and Page 3 of 385 redesign the process to efficiently absorb the rapid technology change expected in DNA sequencing. The MDPM model is used to develop a roadmap of specific multi-domain projects addressing these issues to accelerate the deployment of a national DNA sequencing based surveillance system.by Robert Nicol.Ph.D

Just-In-Time in high variety / low volume manufacturing environments.

Available from British Library Document Supply Centre-DSC:DXN049763 / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo

Annals of Scientific Society for Assembly, Handling and Industrial Robotics

This Open Access proceedings present a good overview of the current research landscape of industrial robots. The objective of MHI Colloquium is a successful networking at academic and management level. Thereby the colloquium is focussing on a high level academic exchange to distribute the obtained research results, determine synergetic effects and trends, connect the actors personally and in conclusion strengthen the research field as well as the MHI community. Additionally there is the possibility to become acquainted with the organizing institute. Primary audience are members of the scientific association for assembly, handling and industrial robots (WG MHI)