Using discrete event simulation for scheduling and long range capacity planning of a high volume press shop

The thesis expresses the essential requirement for and the use of Discrete Event Simulation (DES) in a high volume press shop. The press shop produces blanks and panels for the body shop, which manufactures three car models. DES is used to combat the battle between shop efficiency and low inventory. The process used to choose the most appropriate software package is described and then current situation in the press shop is discussed. The procedures involved in model creation follow set model construction guidelines. There are several assumptions made, which together with the constraints of the system, provide the limitations of the inputs facing the system. There is a trade off between model complexity and accuracy, so the setting of the constraints and assumptions often provided difficult decisions. Validation of the model is very important, so this was a lengthy process, involving using a series of dummy buffers to check inputs such as cycle times and batch quantities. The validated model is used to monitor the methods used to reduce inventory on the shop floor over a period of eight weeks and then used for 'What If? Scenarios, to ascertain the systems capacity and inventory levels underdifferent conditions. The scenarios include using volumes that are 100% higher on some models than the current situation and 20% less than currently. The findings are examined and proposals made for the introduction of the proposed volumes where possible. Findings of the scenarios highlight bottlenecks in the shop and areas for improvement. Using the model, the schedules can be changed quickly and easily to try and eliminate the bottlenecks and improve capacity. Conclusions discuss the problems encountered during the modelling process as well as the benefits. The integration of DES into the current scheduling processes in the shop poses no problems and the model will be used as an aid for capacity planning in the future

Generic proposals to increase productivity using discrete-event simulation for Ford Motor Company

The research project was carried out in conjunction with Ford Motor Company and Cranfield University. This research project has demonstrated partial fulfilment of the requirements for the Master Degree of Science. The project uses discrete simulation techniques to carry out experimentation with an aim of developing generic solutions to increase productivity and output of manufacturing transfer lines within the Ford group. In this highly competitive era for manufacturing where the profit margins tighten each year, Ford and other automotive companies are striving to ensure they produce products that are not only desirable to the consumer but also profitable. Every year senior management at Ford expect an increase in output for each line. This means that investigations must be carried out using simulation to formulate generic ideas and proposals to optimise and increase the output of a number of machining lines. Increasing manufacturing outputs reduces the unit cost per part; therefore there is an increase on the profit margin for each unit sold. Based on the experimental data collected from the research project, three manufacturing lines have been optimised to maximise their productivity. The solutions were then developed into business cases which were produced in line with Ford’s strict investment criteria and as a result each of the three lines should have its annual output increased by more than 5%, with a pay back period of under a year for the required capital investment. A generic solution was found which can potentially optimise any manufacturing line in the Ford Motor Company, providing large increases in annual output to Ford’s manufacturing lines. These solutions will help Ford to maximise its profit contribution per unit sold, securing its place as a leading global automotive manufacturer.MRe

Simulación híbrida como núcleo de simulación de aplicaciones gráficas en tiempo real.

RESUMEN Las aplicaciones gráficas en tiempo real siguen un paradigma de simulación con- tinuo acoplado. Este paradigma presenta diversos inconvenientes, entre ellos cabe destacar el bajo aprovechamiento de la potencia de cálculo de la máquina, la im- posibilidad de de¯nir la QoS de cada objeto y mantenerla durante la ejecución o el acoplo de los procesos de todos los objetos del sistema, en particular el acoplo del proceso de visualización del sistema con el resto de procesos. La tesis propone cambiar el paradigma de simulación de estas aplicaciones a un paradigma discreto desacoplado. Este nuevo paradigma permite solucionar los pro- blemas del paradigma anterior. Los objetos de¯nen su propia QoS independiente- mente del resto del sistema, incluso se permite de¯nir diferentes QoS para diferentes aspectos del propio objeto. Entre estos objetos, est¶a el objeto visualizador, destina- do a controlar el proceso de visualización. El objeto visualizador también de¯ne su propia QoS. En el sistema discreto desacoplado cada objeto consume únicamente la poten- cia de cálculo estrictamente necesaria para llevar a cabo su simulación con la QoS de¯nida. Por ello, la potencia de cálculo del sistema se reparte entre los objetos en función de sus necesidades. El sistema puede adaptarse dinámicamente, rede¯niendo la QoS de los objetos en función de las condiciones de la ejecución del sistema. Los objetos pueden degradar o mejorar su comportamiento durante periodos de la ejecución para evitar colapsos del sistema o para mejorar el comportamiento del sistema. ____________________________________________________________________________________________________Real time graphic applications, speci¯cally videogames, follow a paradigm of continuous simulation that couple the simulation phase and the rendering phase. This paradigm can be ine±cient or it can produce incorrect simulations. It has di- sadvantages, some of them are: the inadequate computer power distribution between the graphic application objects, it is not possible to de¯ne the Quality of Service (QoS) of each application object, the object QoS can be maintained during the ap- plication running, the behavior of all the system objects are coupled (speci¯cally the rendering process and the simulation process). The proposal is to change the simulation paradigm of real time graphic ap- plications. The new simulation paradigm is discrete and decoupled. The use of a decoupled discrete paradigm avoids the problems of the continuous coupled para- digm and it avoids incorrect simulations, besides it improves the simulation quality and e±ciency. The discrete simulation paradigm allows to de¯ne a private QoS crite- rion for each aspect of each object in the videogame. The render object is dedicated to control the application render process. The render object de¯nes its own QoS criteria. It is possible to de¯ne a di®erent sampling frequency for each object aspect in the system. The discrete paradigm allows to de¯ne the objects sampling frequency to distribute the computer power adequately among the objects. The computer power consumed executing the application is only the necessary to guarantee the QoS of each object. The system can be adapted dynamically. The objects QoS can be adjusted to the objects requirements and the whole system requirements, the system load or characteristics. This sampling frequency may change dynamically to adapt the QoS of the object aspect to the real computer power. The result obtained is a discrete system that allows a Smart System Degradation and may rede¯ne dynamically the objects aspects QoS. Objects collect system information and use it to adapt its QoS

An Adaptive Simulation-based Decision-Making Framework for Small and Medium sized Enterprises

Abstract The rapid development of key mobile technology supporting the ‘Internet of Things’, such as 3G, Radio Frequency Identification (RFID), and Zigbee etc. and the advanced decision making methods have improved the Decision-Making System (DMS) significantly in the last decade. Advanced wireless technology can provide a real-time data collection to support DMS and the effective decision making techniques based on the real-time data can improve Supply Chain (SC) efficiency. However, it is difficult for Small and Medium sized Enterprises (SMEs) to effectively adopt this technology because of the complexity of technology and methods, and the limited resources of SMEs. Consequently, a suitable DMS which can support effective decision making is required in the operation of SMEs in SCs. This thesis conducts research on developing an adaptive simulation-based DMS for SMEs in the manufacturing sector. This research is to help and support SMEs to improve their competitiveness by reducing costs, and reacting responsively, rapidly and effectively to the demands of customers. An adaptive developed framework is able to answer flexible ‘what-if’ questions by finding, optimising and comparing solutions under the different scenarios for supporting SME-managers to make efficient and effective decisions and more customer-driven enterprises. The proposed framework consists of simulation blocks separated by data filter and convert layers. A simulation block may include cell simulators, optimisation blocks, and databases. A cell simulator is able to provide an initial solution under a special scenario. An optimisation block is able to output a group of optimum solutions based on the initial solution for decision makers. A two-phase optimisation algorithm integrated Conflicted Key Points Optimisation (CKPO) and Dispatching Optimisation Algorithm (DOA) is proposed for the condition of Jm|STsi,b with Lot-Streaming (LS). The feature of the integrated optimisation algorithm is demonstrated using a UK-based manufacture case study. Each simulation block is a relatively independent unit separated by the relevant data layers. Thus SMEs are able to design their simulation blocks according to their requirements and constraints, such as small budgets, limited professional staff, etc. A simulation block can communicate to the relative simulation block by the relevant data filter and convert layers and this constructs a communication and information network to support DMSs of Supply Chains (SCs). Two case studies have been conducted to validate the proposed simulation framework. An SME which produces gifts in a SC is adopted to validate the Make To Stock (MTS) production strategy by a developed stock-driven simulation-based DMS. A schedule-driven simulation-based DMS is implemented for a UK-based manufacturing case study using the Make To Order (MTO) production strategy. The two simulation-based DMSs are able to provide various data to support management decision making depending on different scenarios