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The ambition of this project is to contribute to the development of optimisation techniques for underground mining. This resulted in a mathematical model to optimise a type of underground transportation system called the ramp. The ramp is a tunnel from the underground mining areas which trucks use to transport material up to the surface. We consider the case where the ramp only fits one truck at a time and it therefore needs passing bays where trucks can meet. We were inspired by an article which optimised the positions of the passing bays and the schedule for the trucks, during a certain time period. We extended that work by proposing a new mathematical model that can handle a more general and complex mine. The result from optimally solving the model gives the positioning of the passing bays and a schedule which completes a number of trips down and up the ramp as quickly as possible. The model can be used both for long-term and short-term planning. The long-term planning regards the positions of the passing bays. The model can therefore be used before the passing bays are constructed to gain insights about where to place them. The short-term planning is about finding an optimal trip schedule given the placement of the passing bays. The model can therefore also be used to provide a haulage schedule for an upcoming time period.

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This research investigates and develops a new approach to the management of service quality with the emphasis on patient and staff satisfaction in the healthcare sector. The challenge of measuring the quality of service in healthcare requires us to view the problem from multiple perspectives. At the philosophical level, the true nature of quality is still debated; at the psychological level, an accurate conceptual representation is problematic; whilst at the physical level, an accurate measurement of the concept still remains elusive to practitioners and academics. This research focuses on the problem of quality measurement in the healthcare sector. The contributions of this research are fourfold: Firstly, it argues that from the technological point of view the research to date into quality of service in healthcare has not considered methods of real-time measurement and monitoring. This research identifies the key elements that are necessary for developing a real-time quality monitoring system for the healthcare environment.Secondly, a unique index is proposed for the monitoring and improvement of healthcare performance using information-theoretic entropy formalism. The index is formulated based on five key performance indicators and was tested as a Healthcare Quality Index (HQI) based on three key quality indicators of dignity, confidence and communication in an Accident and Emergency department. Thirdly, using an M/G/1 queuing model and its underlying Little’s Law, the concept of Effective Satisfaction in healthcare has been proposed. The concept is based on a Staff-Patient Satisfaction Relation Model (S-PSRM) developed using a patient satisfaction model and an empirically tested model developed for measuring staff satisfaction with workload (service time). The argument is presented that a synergy between patient satisfaction and staff satisfaction is the key to sustainable improvement in healthcare quality. The final contribution is the proposal of a Discrete Event Simulation (DES) modelling platform as a descriptive model that captures the random and stochastic nature of healthcare service provision process to prove the applicability of the proposed quality measurement models.

Presented PhD thesis aims at development of new methodologies and approaches to reduce lead times in production systems. Therefore the thesis examines in detail the design of new, more comprehensive approaches to shortening lead times. The dissertation describes the methodology of using these approaches in production systems, it is suggested their inclusion in the control structure of production and adequate managerial support for the successful application of these new approaches in the industry is developed. The first part summarizes current knowledge in the field of reducing lead times. The various methods that can be used for reducing lead times are defined and described, from which is selected discrete simulation of manufacturing systems as a suitable method for the purposes of issue development. The next part of this work is therefore devoted to simulation approach to reducing lead times and the factors that affect them, such as processing time, size of the batch, queue lengths, etc. In this part is also discussed the use of information technologies (programming languages, libraries, and software tools) that enable efficient creation of simulation models. The second part is focused on industrial applications implemented to reduce production lead times. Specific simulation analysis deal with, for example, reduction of the lead time for manufacture of surgical instruments, screws, slats, but also transport systems, optimization of production orders input to the production system, the issue of supply, etc. The second part also describes a practical approach to data transfer to / from the simulation model, simulation software connection to the ERP database of enterprise and energy intensity of production. The conclusion summarizes the findings that were detected on the issue of reducing lead times, and within the chosen methodology, simulation of manufacturing processes indicates possible further progress in the research and practical applications.