The clothing industry is multifaceted and is characterised by garments with a short life cycle, unstable customer needs and varying fashion styles. This affects the accuracy of demand planning. In SA, the clothing industry has experienced a decline in the number of clothing manufacturers and manufacturing outputs as well as fluctuations in employment. This study investigates demand planning practices in the Gauteng clothing industry. A descriptive and exploratory study was conducted based on a semi-structured questionnaire. The structured data was descriptively analysed using SPSS and inferentially analysed using the Kruskal‒Wallis test as well as content analysis for the unstructured questions. The findings revealed that demand planning practices in the Gauteng clothing industry are conducted using the hierarchical and optimal demand planning approaches. The results also revealed that there are certain factors which affect the way demand planning is conducted in the clothing industry in Gauteng. These factors includes: scheduling, fashion clothes, point of sale system, imports, estimation, recession and lead time. Furthermore, the study revealed that there are differences in the factors affecting demand planning regarding the three key clothing stakeholders (fabric suppliers, clothing manufacturers and fashion designers). The study revealed that key demand planning practices employed in the Gauteng clothing industry are production planning, uncertainty prevention, forecasting and production machine capabilities. These practices are important attributes of the hierarchical and optimal demand planning approaches. The study recommends that the hierarchical demand planning approach is more effective when planning for basic clothes (which involved planning horizon of twelve months), while the optimal demand planning approach is effective when planning for fashion clothes (which involved planning horizon of six months). The study recommends that the Gauteng clothing industry should consider factors which affect demand planning when planning for customers' needs as they affect the level of productivity in the organisation. / Entrepreneurship Supply Chain Transport Tourism and Logistics Management / M. Com.(Logistics)

Transport demand planning in South Africa is a neglected field of study, using obsolete methods to model an extremely complex, dynamic system composed of an eclectic mix of First and Third World transport technologies, infrastructure and economic participants. We identify agent-based simulation as a viable modelling paradigm capable of capturing the effects emerging from the complex interactions within the South African transport system, and proceed to implement the Multi-Agent Transport Simulation Toolkit (MATSim) for South Africa's economically important Gauteng province. This report describes the procedure followed to transform household travel survey, census and Geographic Information System (GIS) data into an activity-based transport demand description, executed on network graphs derived from GIS shape files. We investigate the influence of network resolution on solution quality and simulation time, by preparing a full network representation and a small version, containing no street-level links. Then we compare the accuracy of our data-derived transport demand with a lower bound solution. Finally the simulation is tested for repeatability and convergence. Comparisons of simulated versus actual traffic counts on important road network links during the morning and afternoon rush hour peaks show a minimum mean relative error of less than 40%. Using the same metric, the small network differs from the full representation by a maximum of 2% during the morning peak hour, but the full network requires three times as much memory to execute, and takes 5.2 times longer to perform a single iteration. Our census- and travel survey-derived demand performs significantly better than uniformly distributed random pairings of home- and work locations, which we took to be analogous to a lower bound solution. The smallest difference in corresponding mean relative error between the two cases comes to more than 50%. We introduce a new counts ratio error metric that removes the bias present in traditional counts comparison error metrics. The new metric shows that the spread (standard deviation) of counts comparison values for the random demand is twice to three times as large as that of our reference case. The simulation proves highly repeatable for different seed values of the pseudo-random number generator. An extended simulation run reveals that full systematic relaxation requires 400 iterations. Departure time histograms show how agents 'learn' to gradually load the network while still complying with activity constraints. The initial implementation has already sparked further research. Current priorities are improving activity assignment, incorporating commercial traffic and public transport, and the development and implementation of the minibus taxi para-transit mode. Copyright / Dissertation (MEng)--University of Pretoria, 2009. / Industrial and Systems Engineering / unrestricted

Over the years a significant decline in employment had occurred in the Douglas-fir region’s lumber and wood products industry. High levels of unemployment can lead to undesirable economic and social effects. An understanding of the nature of unemployment can facilitate future planning as well as mitigating current problems. This study has attempted to examine the underlying causes of employment decline in the region’s softwood lumber and plywood industries, specifically over the period 1979-86. This time span is of particular importance since there was a rapid decline in employment levels after 1979. There has been much controversy over the causes of this reduction but no comprehensive empirical analysis was ever undertaken to determine its cause. Meanwhile levels of output, which also declined in the early part of this span, have again reached pre-recession levels. A cost function approach was employed as the basis of the empirical analysis. The results suggest that most of the employment decline in these industries has been caused by changes in the structure of production and by increasing labour productivity. Although there are indications of cyclical unemployment, much of the reduction in the industries' labour force seems to be attributable to greater substitution of capital and logs for labour. Simulation analyses tend to suggest that changes in factor prices would not have had any dramatic effect on employment levels. It was found that of the recent employment decline in the two industries, around one-quarter of the loss in the lumber industry and one-third in the plywood industry are caused by cyclical forces. Structural factors were assumed to be the cause of the remaining loss in levels of labour input.

Various forecasting tools, based on historical data, exist for planners of national networks that are very effective in planning national interventions to ensure energy security, and meet carbon obligations over the long term. However, at a local community level, where energy demand patterns may significantly differ from the national picture, planners would be unable to justify local and more appropriate intervention due to the lack of appropriate planning tools. In this research, a new methodology is presented that initially creates a virtual community of households in a small community based on a survey of a similar community, and then predicts the energy behaviour of each household, and hence of the community. It is based on a combination of the statistical data, and a questionnaire survey. The methodology therefore enables realistic predictions and can help local planners decide on measures such as embedding renewable energy and demand management. Using the methodology developed, a study has been carried out in order to understand the patterns of electricity consumption within UK households. The methodology developed in this study has been used to investigate the incentives currently available to consumers to see if it would be possible to shift some of the load from peak hours. Furthermore, the possibility of using renewable energy (RE) at community level is also studied and the results presented. Real time pricing information was identified as a barrier to understanding the effectiveness of various incentives and interventions. A new pricing criteria has therefore been developed to help developers and planners of local communities to understand the cost of intervention. Conclusions have been drawn from the work. Finally, suggestions for future work have been presented. / Libyan government

Master of Science / Department of Agricultural Economics / Hikaru H. Peterson / Farmer-to-consumer direct marketing institutions have expanded significantly in the last decades. In particular, Community Supported Agriculture (CSA) has developed exponentially in the US and in Europe. CSAs consist of a contract in which the consumer buys a share of the farm production at the beginning of the season and receive in exchange a bundle of products regularly. CSAs still account for a marginal share of food sales today and many questions remain unanswered, such as the level of knowledge of the general public about CSA, the potential size of the market, its consumer characteristics, and the main motivations and barriers that lead consumers to either join or not join CSAs. This study focused on addressing these questions for the Kansas City area and the central region in France. Another objective was to give recommendations to farmers on how to develop CSAs. Two versions of the surveys were designed and conducted in the US and in France to address the objectives. Particularly, two types of questions were used in order to elicit willingness to pay (WTP): an open-ended question and a choice experiment. A Tobit model and discrete choice models were run to analyze results from the open-ended question and the choice experiment, respectively. Results show that around 80 percent of the population knew little about CSAs. The understanding of the demand for CSAs shows that a potential market, accounting for around 25 percent of the population, exists, but consumers are very exigent and farmers need to provide well-considered contracts to attract consumers. Recommendations to farmers are presented following the 4P method. For the Product, the variety offered seems to be the most important point. For Price, it has been estimated from the demand at $300 in the US and €400 in France for a basic share. Promotion would need to focus on education. Having various delivery locations would be the best option concerning Place; home delivery was found to be unnecessary. Tendencies found in the US and in France were similar except for educational activities: the French are looking more for these opportunities than Americans who care more about convenience.

Typescript (photocopy). / Digitized by Kansas Correctional Industries

Call number: LD2668 .T4 1958 M68

Call number: LD2668 .T4 1955 M36 / Master of Science

South Africa’s electricity supply is under pressure because of inadequate capacity expansion in the early 2000s. One of the initiatives funded by Eskom to alleviate the pressure on the national electricity grid was an aggressive demand-side management (DSM) programme that commenced in 2004. A positive outcome of the DSM programme was that the industrial sector in South Africa benefited from the implementation of a relatively large number of DSM projects. These DSM projects reduced the electricity costs of industrial clients and reduced the demand on the national electricity grid. Unfortunately, the performance of industrial DSM projects deteriorates without proper maintenance. This results in wasted savings opportunities that are costly to industrial clients and Eskom. The purpose of this study was therefore to develop a maintenance strategy that could be applied, firstly, to reverse the deterioration of DSM project performance and, secondly, to sustain and to improve DSM project performance. The focus of the maintenance strategy was to obtain maximum project performance that translated to maximum electricity cost savings for the client. A new performance-centered maintenance (PCM) strategy was developed and proven through practical experience in maintaining industrial DSM projects over a period of more than 60 months. The first part of the PCM strategy consisted of developing a new strategy for the outsourcing of DSM project maintenance to energy services companies (ESCOs) on the company group level of the client. The strategy served as a guideline for both ESCOs and industrial clients to implement and manage a group-level DSM maintenance agreement successfully. The second part of the PCM strategy consisted of a simplified method that was developed to identify DSM projects where applying a PCM strategy would increase or sustain electricity cost savings. The third part of the PCM strategy consisted of practical maintenance guidelines that were developed to ensure maximum project performance. It was based on the plan-do-check-act cycle for continuous improvement with an emphasis on the monitoring of DSM project performance. The last part of the PCM strategy consisted of various alternative key performance indicators that should be monitored to ensure maximum sustainable DSM project performance. The PCM strategy was evaluated by implementing it on ten different DSM projects. The results showed that applying a PCM strategy resulted in an average increase of 64.4% in the electricity cost savings generated by these projects. The average implementation cost of the PCM strategy was 6% of the total benefit generated through it. This indicated that implementing the PCM strategy was a cost-effective manner to ensure that maximum performance of DSM projects was maintained sustainably. / PhD (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2015

Costs saving measures are important for South African gold producers due to increasing energy costs and decreasing production volumes. Demand Side Management (DSM) is an effective strategy to reduce electricity consumption and costs. DSM projects have been implemented widely on South African mining systems such as pumping, refrigeration, rock transport and compressed air. Implementations have, however, been limited on gold processing plants despite the significant amounts of energy that this section consumes. The main objective of gold processing plants is production orientated and energy management is not a primary focus. This rationale is re-evaluated owing to high electricity price inflation and availability of DSM incentives. This study investigated the cost saving potential of DSM interventions on gold plants. Electrical load management was identified as a key opportunity that can deliver substantial cost savings. These savings were shown to be feasible in respect of the required capital expenditure, effort of implementation and maintenance of operational targets. Investigation procedures were compiled to identify feasible load management opportunities. The most potential for electricity cost savings was identified on comminution equipment. Consequently, a methodology was developed to implement electrical load management on the identified sections. The methodology proposed simulation techniques that enabled load management and subsequent electricity cost optimisation through production planning. Two electrical load management case studies were successfully implemented on comminution equipment at two gold processing plants. Peak period load shift of 3.6 MW and 0.6 MW, respectively, was achieved on average for a period of three months. The annual cost savings of these applications could amount to R1.4-million and R 660 000. This results in specific electricity cost reductions of 3% and 7% for the two respective case studies. Results from the two case studies are an indication of potential for electrical load management on South African gold processing plants. If an average electricity cost saving of 5% is extrapolated across the South African gold processing industry, the potential cost savings amount to R 25-million per annum. Although the costs saving opportunities are feasible, it is influenced by the reliability of the equipment and the dynamics of ore supply. This insight plays a decisive role in determining the feasibility of DSM on gold processing plants. / MIng (Mechanical Engineering), North-West University, Potchefstroom Campus, 2015