Several analytical techniques including use case diagrams, process flow diagrams (PFDs), hierarchical task analysis (HTA), failure mode and effects analysis (FMEA), systematic human error reduction and prediction approach (SHERPA), hazard analysis and critical control point (HACCP), heuristics, the Safe Living Guide and the Resident Assessment Instrument – Home Care (RAI-HC) are applied to data obtained from two pilot home visits to determine whether common failure modes, causes, effects and recommendations are yielded by the techniques. The time required to apply each analytical technique to processes uncovered from the pilot data was measured and outputs of the techniques were reviewed for commonality. Of the tools considered, SHERPA was found to return the most failure modes, effects and recommendations, while FMEA was the only human factors tool to yield causes. Additionally, FMEA and SHERPA provided a means of ranking potential failure modes based on severity and probability.

Several analytical techniques including use case diagrams, process flow diagrams (PFDs), hierarchical task analysis (HTA), failure mode and effects analysis (FMEA), systematic human error reduction and prediction approach (SHERPA), hazard analysis and critical control point (HACCP), heuristics, the Safe Living Guide and the Resident Assessment Instrument – Home Care (RAI-HC) are applied to data obtained from two pilot home visits to determine whether common failure modes, causes, effects and recommendations are yielded by the techniques. The time required to apply each analytical technique to processes uncovered from the pilot data was measured and outputs of the techniques were reviewed for commonality. Of the tools considered, SHERPA was found to return the most failure modes, effects and recommendations, while FMEA was the only human factors tool to yield causes. Additionally, FMEA and SHERPA provided a means of ranking potential failure modes based on severity and probability.

This dissertation reports the investigation and combination of optimization methodologies and the result of implementing them within a production environment. A literature survey was conducted on the optimization methodologies Lean Manufacturing and theory of constraints (TOC). A number of production optimization methodologies were studied and considered for application to the case study organisation. Due to the small size and relative simplicity of the operation, these methodologies had to be simplified and combined into a more relevant form. A refractory manufacturer was used as a case study for the investigation into the optimization of the dry batch plant. Lean Manufacturing and TOC are optimization methodologies that could be employed to optimize the dry batch plant. Tools from these methodologies were used to investigate problems identified within the production process that were causing the batching plant to perform non-optimally. A time and motion study was conducted and a process flow chart was created to understand the production process. Wasteful activities were identified using a value stream map and a flow process chart was used to visualise the movement within the production process. A 5-Why analysis was conducted to determine the root causes. An optimization plan was created to eliminate the wasteful activities and the operational measures, that is throughput, inventory and operating expense, were used as to determine what the effect the optimization plan would have on the wasteful activities (Lean Manufacturing) found within the batching plant and the organisation. The results of the combined effect of the optimization plan are discussed focusing on the improvements in the operational measures and the increase in profit from sales. Future research is suggested to improve the benchmarking of the optimization plan and any future improvements that the organisation might implement. / MSc (Development and Management Engineering), North-West University, Potchefstroom Campus, 2015

This dissertation reports the investigation and combination of optimization methodologies and the result of implementing them within a production environment. A literature survey was conducted on the optimization methodologies Lean Manufacturing and theory of constraints (TOC). A number of production optimization methodologies were studied and considered for application to the case study organisation. Due to the small size and relative simplicity of the operation, these methodologies had to be simplified and combined into a more relevant form. A refractory manufacturer was used as a case study for the investigation into the optimization of the dry batch plant. Lean Manufacturing and TOC are optimization methodologies that could be employed to optimize the dry batch plant. Tools from these methodologies were used to investigate problems identified within the production process that were causing the batching plant to perform non-optimally. A time and motion study was conducted and a process flow chart was created to understand the production process. Wasteful activities were identified using a value stream map and a flow process chart was used to visualise the movement within the production process. A 5-Why analysis was conducted to determine the root causes. An optimization plan was created to eliminate the wasteful activities and the operational measures, that is throughput, inventory and operating expense, were used as to determine what the effect the optimization plan would have on the wasteful activities (Lean Manufacturing) found within the batching plant and the organisation. The results of the combined effect of the optimization plan are discussed focusing on the improvements in the operational measures and the increase in profit from sales. Future research is suggested to improve the benchmarking of the optimization plan and any future improvements that the organisation might implement. / MSc (Development and Management Engineering), North-West University, Potchefstroom Campus, 2015

<p>The internal and external challenges construction companies face such as variability, low productivity, inefficient processes, waste, uncertainties, risks, fragmentation, adversarial contractual relationships, competition, and those resulting from internal and external challenges such as cost overruns and delays negatively affect company performance and profitability. Though research publications abound, these challenges persist, which indicates that the following gaps exist. Lean construction, process improvement, and performance improvement research have been conducted wherein improvement principles, and best practices are used to ameliorate performance issues, but several knowledge gaps exist. Few companies use these improvement principles and best practices. For those companies applying improvements, there is no established link between these improvements and performance/profitability to guide companies. Further, even when companies use improvement principles and best practices, they apply only one or two, whereas an integrated application of these improvement principles and best practices would be more effective. The other gap the author identified is the lack of strategic tools that construction companies can use to improve and manage their profitability. This thesis tried to fill the knowledge gap, at least partially, by developing a two-part excellence model for profitability improvement of construction companies. The excellence model lays out strategies that would enable companies to overcome the challenges and improve their profitability. The excellence model also gives an iterative and recursive continuous improvement model and flowchart to improve the profitability of construction companies. The researcher used high impact principles, guidelines, and concepts from the literature on organizational effectiveness, critical success factors, strategic company profitability growth enablers, process improvement, and process maturity models, performance improvement, and organizational excellence guidelines to develop the two-part excellence model.</p> <p>The author also translated the two-part excellence model into the diagnostic tool and Decision Support System (DSS) by use of process diagrams, fishbone diagrams, root cause analysis, and use of improvement principles, countermeasures and best practices at the most granular (lowest intervention) levels to do away with root causes of poor performance. The author developed the diagnostic tool and Decision Support System (DSS) in Access 2016 to serve as a strategic tool to improve and manage the profitability of construction companies. The researcher used improvement principles, and best practices from scientific and practitioner literature to develop company and project process flow diagrams, and fishbone (cause and effect) diagrams for company, department, employee, interactions and project performance for the profitability improvement, which are the engines of the diagnostic tool and DSS. The diagnostic tool and DSS use continuous improvement cycles iteratively and recursively to improve the profitability of construction companies from the current net profit of 2-3 percent to a higher value.</p>

The wastewater treatment plays an important role in the maintenance of natural water resources. However, regardless of the technology used or the level of treatment required, the treatment plants of the XXI century are highly complex systems that not only need to meet technical requirements, but also environmental and economic criteria. In this context, decision support systems for environmental domains (English, Environmental Decision Support Systems or EDSS) are configured as an effective tool to support the selection and evaluation of integrated water treatment alternatives. The EDSS designed can be defined as interactive software, flexible and adaptable, which links the numerical models / algorithms, techniques and environmental ontologies, knowledge-based environment, and is capable of supporting decision making, either in choosing between different alternatives, improving potential solutions, or in the integrated assessment using methodologies ranging from environmental (Life Cycle Analysis) to economic / La depuració d’aigües residuals juga un paper fonamental en el manteniment dels recursos hídrics naturals. Tanmateix, sigui quina sigui la tecnologia emprada o el nivell de depuració requerit, les plantes de tractament del segle XXI són sistemes d’alta complexitat, que no només han de satisfer requeriments de tipus tècnic, sinó també de tipus ambiental i econòmic. En aquest context, els sistemes de suport a la decisió en dominis ambientals (en anglès, Environmental Decision Support Systems o EDSS) es configuren com una eina eficaç per donar suport a la selecció i a l’avaluació integrada de diferents alternatives de depuració d’aigües. El EDSS dissenyat pot definir-se com un programari interactiu, flexible i adaptable, que vincula els models numèrics/algoritmes amb tècniques basades en el coneixement i ontologies ambientals, i que és capaç de donar suport a la presa de decisió, ja sigui en l’elecció entre diferents alternatives, millorant una solució, o bé en l’avaluació integrada a través de metodologies ambientals (Anàlisi de Cicle de Vida) i econòmiques