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In a market environment that is subject to continuous changes, companies need to adapttheir production systems in order to maintain the competitive edge. Current literatureshows that with a successful production system design, higher levels of output, eciencyand quality can be achieved.However, designing a production system is done infrequently and therefore tends tolack experience. As a result, design decisions have to be made under uncertainty due toa lack of information, structure and knowledge. In fact, the success of a design process isdirectly linked to the level of uncertainty.The purpose of this thesis is to reduce uncertainty in production system design throughDiscrete Event Simulation before an assembly system is implemented. Therefore, a theoreticalstudy was carried out dening types and sources of uncertainty in productionsystem design. Parallel to the theoretical study, a case study in Volvo ConstructionEquipment Operations Hallsberg was conducted. Discrete Event Simulation was testedas a tool to reduce uncertainty in production system design.The analysis illustrates the observed sources of uncertainty in production systemdesign cover a process, organizational, corporate, market and cultural context.The relevant uncertainty types identied in the case study in Volvo ConstructionEquipment Operations Hallsberg were environmental, system, technical, structural,temporal, lack of knowledge and lack of information. The information providedby the Discrete Event Simulation in order to reduce uncertainty are in form ofKPIs, process structure and visualization. The provided information had a positiveimpact on the degree of technical uncertainties, the lack of knowledge and thelack of information. As a result, the level of uncertainty in the Volvo ConstructionEquipment Operations Hallsberg future line designing process was reduced.

Solar power systems are becoming increasingly popular due to the fact that solar power can offer time and money saving solutions for off-grid and grid-connected homes, cabins, and businesses with clean and affordable energy. However, there are still significant opportunities to reduce the cost of solar power systems by optimizing system design. This paper presents a methodology for evaluating the lifecycle labor costs of solar power systems. This methodology can help optimize system designs relative to cost. It can also support solar power system selection decisions based on a holistic lifecycle view. The methodology accomplishes this by first presenting a method to evaluate the modularity of competing systems, or design variants. It then describes a method of gathering data and modeling the systems so that it can be communicated to relevant stakeholders. Finally, it uses discrete event simulation to generate an estimate of relative lifecycle labor cost performance. Verification and validation of the methods described are presented through a case study of the MegaModule residential solar power system, designed by the team at GTRI. The paper concludes with a review of limitations and proposed future work.

Assembly lines are no longer systems designed to produce as much as possible at the lower cost. Nowadays several factors such as mass customization and variation in demand have led the manufacturers to consider the flexibility of the assembly systems as one of the most important facts to take into account when designing an assembly line. In this context, this study attempts to test a new paradigm of the workload balance, which is based on a dynamic allocation of the assembly operations. In order to test the hypothesis, a real assembly system of engines has been used as a base model to implement the new approach. The work developed, uses the simulation as a means to carry out the study, which has required the development of several simulation scenarios. The hypothesis has been studied from two different approaches; on one hand a total dynamic allocation of assembly operations, which was expected to cause a wide operational range of the stations. On the other hand, the second approach implements a flow control which aims to reduce the operational range and workload fluctuations. The results obtained show a significant improvement of the system performance in comparison with the current assembly line. It has been found that any improvement implemented in the system is directly reflected in the total performance of the line, regardless if the improvement is made in a system constraint. Moreover, the results have proven a better response of the system to changes in the frequency of models production.  Finally, based on the results, this study suggests several paths of future work in order to acquire the needed information to implement the hypothesis in the real world context. / Flexa project

High profit (low volume) products are very attractive economically, and are influencing the direction of manufacture towards product based batch processes. One new system which has a great deal of potential is a "pipeless" plant, in which the reactor moves to different areas of the plant where heating, agitation etc. takes place. There are obvious advantages in its use in providing a means of quickly responding to fast market changes while maintaining high product quality with reduced waste. The basic concept has been successfully demonstrated with several production plants already in operation, mainly in Japan. Nevertheless the safety issues associated with pipeless plants have not been dealt with. Three main areas of further work have been identified in the safe design of computer controlled pipeless batch plants: process, computer control, and scheduling safety. In essence it is a batch process that is carried out, and therefore entails all the safety issues associated with a batch process, such as the sharing of resources. As with all new processes, it is necessary to identify and eliminate as many hazards as possible at the design stage. Computers can introduce hazards as well as benefits. There is extensive use of computer control in automated pipeless plants, and the primary manner in which problems occur is through hardware and software failures. Possible hazards need to be identified and eliminated at the design stage, without losing the benefits of plant flexibility and speed of product changeover. Scheduling is usually concerned with optimum product output, and does not consider safety. One of the biggest problems with moving reactors is collisions. To overcome, or minimise the possibility of this problem, the plant layout and schedule require careful consideration. Simulation is a very useful tool for demonstrating the interaction between the two. The aim of this research is to develop an integrated approach to hazard identification and safety requirement specification. The results of which should be a methodology that allows the user to produce a safe design for an economically attractive pipeless plant for batch processes.

Compliance, the extent to which patients follow a medication regimen, has been recognized as one of the most serious problems facing medical practice today. Recent developments in assessing compliance include electronic compliance monitors (ECM), devices that record the date and time of the release of medication from its original container. This allows utilizing ECM compliance data in statistical analyses related to clinical trials. This thesis proposes ways of dealing with the time-varying nature of compliance. We examine the compliance behaviour from real ECM data through statistical analysis of compliance rate, followed by a time-to-event analysis with respect to first noncompliance event. Then, using discrete event simulation and proportional hazards models we compare analyses using a fixed treatment covariate and time-varying compliance covariate based on pharmacokinetic principles in estimating treatment effect. We observe a reduction of up to 40% in EMSE in favour of the latter model for treatment effect estimation.

Research shows that in a system model, when the production rate is adjusted based on the number of items in queue, the nature of the model changes from an open-loop queueing system to a closed-loop feedback control system. Service-rate adjustment can be implemented in a discrete event simulation model, but the effect of this adjustment has not been thoroughly analyzed in the literature. This research considers the design of feedback signals to generate realistic simulation models of production system behavior. A series of simulation experiments is conducted to provide practical guidance for simulation modelers on how adding a service-rate adjustment feedback loop to a queueing system affects system performance.

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The vast majority of the research efforts in finite capacity scheduling over the past several years has focused on the generation of precise and almost exact measures for the working schedule presupposing complete information and a deterministic environment. During execution, however, production may be the subject of considerable variability, which may lead to frequent schedule interruptions. Production scheduling mechanisms are developed based on centralised control architecture in which all of the knowledge base and databases are modelled at the same location. This control architecture has difficulty in handling complex manufacturing systems that require knowledge and data at different locations. Adopting biological control principles refers to the process where a schedule is developed prior to the start of the processing after considering all the parameters involved at a resource involved and updated accordingly as the process executes. This research reviews the best practices in gene transcription and translation control methods and adopts these principles in the development of an autonomous finite capacity scheduling control logic aimed at reducing excessive use of manual input in planning tasks. With autonomous decision-making functionality, finite capacity scheduling will as much as practicably possible be able to respond autonomously to schedule disruptions by deployment of proactive scheduling procedures that may be used to revise or re-optimize the schedule when unexpected events occur. The novelty of this work is the ability of production resources to autonomously take decisions and the same way decisions are taken by autonomous entities in the process of gene transcription and translation. The idea has been implemented by the integration of simulation and modelling techniques with Taguchi analysis to investigate the contributions of finite capacity scheduling factors, and determination of the ‘what if’ scenarios encountered due to the existence of variability in production processes. The control logic adopts the induction rules as used in gene expression control mechanisms, studied in biological systems. Scheduling factors are identified to that effect and are investigated to find their effects on selected performance measurements for each resource in used. How they are used to deal with variability in the process is one major objective for this research as it is because of the variability that autonomous decision making becomes of interest. Although different scheduling techniques have been applied and are successful in production planning and control, the results obtained from the inclusion of the autonomous finite capacity scheduling control logic has proved that significant improvement can still be achieved.