Thesis (M.S.)--University of Wisconsin--Madison, 1984. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 81-83).

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Electrical machines form part of our everyday life at home and in industry plants. Currently induction machines are the backbone of the industry machine installation as these are robust, reliable and have relatively high efficiency. However as the price of energy increases and stricter efficiency regulations are put into place there is a need for more efficient electrical machines. The majority of induction machines on Sasol's plants are between 2.2 kW and 22 kW. Of these, 95% machines are connected to pump loads and 2% to fan loads. Thus the majority of the machines operate at a constant speed. Rather than try to improve an induction machine, this project proposes the design for a more efficient LS PMSM that can also be used in the same applications as mentioned above. Although LS PMSMs aren’t a new concept, the demand and industry interest in this technology has increased in recent years. Since 2000 the number of research publications with regards to this machine has increased significantly. The goal of this project is to gain a better understanding of these machines by designing a prototype. The design entitles the stator and rotor. As Sasol provided the funding for the project it was decided to design a three phase, 7.5 kW 525V, four-pole machine. During the design phase several design techniques done by other researchers were incorporated into the prototypes. The design is done with the aid of two FEM software packages namely FEMM and ANSYS Maxwell® and verified against calculated values. The final prototype is tested and compared to the predicted values determined during the design. An industry available LS PMSM from Weg, the WQuattro is also used to compare the results of the prototype. The prototype machine’s no-load, full load and locked rotor behaviour is tested as well as the back-emf waveform. From the results gained the machine is validated. The machine did not perform as predicted and further investigation into the reason is needed. Due to the incorrect wiring of the stator and some other rotor manufacturing issues the prototype cannot be fully validated. However it was found that several of the designed values correlated to the measured values. Further investigation into the under performances as well as more relevant testing and practical manufacturing method is needed. / MIng (Electrical and Electronic Engineering), North-West University, Potchefstroom Campus, 2014

Electrical machines form part of our everyday life at home and in industry plants. Currently induction machines are the backbone of the industry machine installation as these are robust, reliable and have relatively high efficiency. However as the price of energy increases and stricter efficiency regulations are put into place there is a need for more efficient electrical machines. The majority of induction machines on Sasol's plants are between 2.2 kW and 22 kW. Of these, 95% machines are connected to pump loads and 2% to fan loads. Thus the majority of the machines operate at a constant speed. Rather than try to improve an induction machine, this project proposes the design for a more efficient LS PMSM that can also be used in the same applications as mentioned above. Although LS PMSMs aren’t a new concept, the demand and industry interest in this technology has increased in recent years. Since 2000 the number of research publications with regards to this machine has increased significantly. The goal of this project is to gain a better understanding of these machines by designing a prototype. The design entitles the stator and rotor. As Sasol provided the funding for the project it was decided to design a three phase, 7.5 kW 525V, four-pole machine. During the design phase several design techniques done by other researchers were incorporated into the prototypes. The design is done with the aid of two FEM software packages namely FEMM and ANSYS Maxwell® and verified against calculated values. The final prototype is tested and compared to the predicted values determined during the design. An industry available LS PMSM from Weg, the WQuattro is also used to compare the results of the prototype. The prototype machine’s no-load, full load and locked rotor behaviour is tested as well as the back-emf waveform. From the results gained the machine is validated. The machine did not perform as predicted and further investigation into the reason is needed. Due to the incorrect wiring of the stator and some other rotor manufacturing issues the prototype cannot be fully validated. However it was found that several of the designed values correlated to the measured values. Further investigation into the under performances as well as more relevant testing and practical manufacturing method is needed. / MIng (Electrical and Electronic Engineering), North-West University, Potchefstroom Campus, 2014

M.Phil. (Electrical & Electronic Engineering Science) / The need to industrialise South Africa has been an effort of government to increase manufacturing and Gross Domestic Products (GDP) while also creating decent work. Manufacturing industry has been striking with organisations closing and moving. Organisations have been established and fail to compete in the market due to lack of expertise to produce products that meet the customer`s requirements. Due to the opportunities of industrialisation in Africa the focus to develop equipment for these industries is necessary. This research objective is to develop a Systematic Approach of Product Development for Industrial Processing Equipment manufacturers that supply various organisations. The research will respond to the following question while also defining the development process:-  Will product development be helpful in industrialising South Africa and building sustainable manufacturing businesses?  Define a process feedback diagram of a systematic approach of product development to be used by industrial processing equipment? The research is done with the use of literature review form published sources which is validated by survey questions that were sent to sustainable successful organizations that supply industrial equipment. The research finding demonstrates the success phases and steps to be followed when developing product. The phases and their steps are;- 1. Marketing phase stages are Identifying Market Opportunities, Evaluating Potential Markets, Identifying Customer`s Needs and Product specification 2. Concept Development phase stages are system engineering for requirements identification & allocations, Internal & external Search of solution, concept selection and concept testing 3. System Level Design phase stages is Product Architecture 4. Detailed Design Phase stages are industrial design and design for manufacturing 5. Refinement and testing phase stages are designing for reliability, prototyping and testing. These are the phases the research focused on. The Survey revealed that success sustainable organisation have been using product development, marketing and system engineering methodologies as one of their common weapon to stay in business and grow in today’s competitive market place. This systematic approach process feedback diagram in product development has a lot of phase overlap. All phases interact even though there is still a feed process from one phase to the next. The process happens concurrently to ensure that all stages are considered at an earlier stage

The aim of this master thesis is the construction of a single-purpose semi-automatic machine to assembly a component of a car. The component of assemble is a device to refueling, which consists of more thermoplastic parts. It is used a knowledge of 3D modeling software, solution of construction assemblies and necessary calculations to design the machine. The result of this thesis is detailed 3D model and drawing documentation of designed assembly machine.

The efficacy of a machine learning technique is domain dependent. Some machine learning techniques work very well for certain domains but are ill-suited for other domains. One area that is of real-world concern is the flexibility with which machine learning techniques can adapt to dynamic domains. Currently, there are no known reports of any system that can learn dynamic domains, short of starting over (i.e., re-running the program). Starting over is neither time nor cost efficient for real-world production environments. This dissertation studied a method, referred to as Experience Based Learning (EBL), that attempts to deal with conditions related to learning dynamic domains. EBL is an extension of Instance Based Learning methods. The hypothesis of the study related to this research was that the EBL method would automatically adjust to domain changes and still provide classification accuracy similar to methods that require starting over. To test this hypothesis, twelve widely studied machine learning datasets were used. A dynamic domain was simulated by presenting these datasets in an uninterrupted cycle of train, test, and retrain. The order of the twelve datasets and the order of records within each dataset were randomized to control for order biases in each of ten runs. As a result, these methods provided datasets that represent extreme levels of domain change. Using the above datasets, EBL's mean classification accuracies for each dataset were compared to the published static domain results of other machine learning systems. The results indicated that the EBL's system performance was not statistically different (p>0.30) from the other machine learning methods. These results indicate that the EBL system is able to adjust to an extreme level of domain change and yet produce satisfactory results. This finding supports the use of the EBL method in real-world environments that incur rapid changes to both variables and values.

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Within any manufacturing environment, the selection of the production or assembly machines is part of the day to day responsibilities of management. This is especially true when there are multiple types of machines that can be used to perform each assembly or manufacturing process. As a result, it is critical to find the optimal way to select machines when there are multiple related assembly machines available. The objective of this research is to develop and present a model that can provide guidance to management when making machine selection decisions of parallel, non-identical, related electronics assembly machines. A model driven Decision Support System (DSS) is used to solve the problem with the emphasis in optimizing available resources, minimizing production disruption, thus minimizing cost. The variables that affect electronics product costs are considered in detail. The first part of the Decision Support System was developed using Microsoft Excel as an interactive tool. The second part was developed through mathematical modeling with AMPL9 mathematical programming language and the solver CPLEX90 as the optimization tools. The mathematical model minimizes total cost of all products using a similar logic as the shortest processing time (SPT) scheduling rule. This model balances machine workload up to an allowed imbalance factor. The model also considers the impact on the product cost when expediting production. Different scenarios were studied during the sensitivity analysis, including varying the amount of assembled products, the quantity of machines at each assembly process, the imbalance factor, and the coefficient of variation (CV) of the assembly processes. The results show that the higher the CV, the total cost of all products assembled increased due to the complexity of balancing machine workload for a large number of products. Also, when the number of machines increased, given a constant number of products, the total cost of all products assembled increased because it is more difficult to keep the machines balanced. Similar results were obtained when a tighter imbalance factor was used.

Within any manufacturing environment, the selection of the production or assembly machines is part of the day to day responsibilities of management. This is especially true when there are multiple types of machines that can be used to perform each assembly or manufacturing process. As a result, it is critical to find the optimal way to select machines when there are multiple related assembly machines available. The objective of this research is to develop and present a model that can provide guidance to management when making machine selection decisions of parallel, non-identical, related electronics assembly machines. A model driven Decision Support System (DSS) is used to solve the problem with the emphasis in optimizing available resources, minimizing production disruption, thus minimizing cost. The variables that affect electronics product costs are considered in detail. The first part of the Decision Support System was developed using Microsoft Excel as an interactive tool. The second part was developed through mathematical modeling with AMPL9 mathematical programming language and the solver CPLEX90 as the optimization tools. The mathematical model minimizes total cost of all products using a similar logic as the shortest processing time (SPT) scheduling rule. This model balances machine workload up to an allowed imbalance factor. The model also considers the impact on the product cost when expediting production. Different scenarios were studied during the sensitivity analysis, including varying the amount of assembled products, the quantity of machines at each assembly process, the imbalance factor, and the coefficient of variation (CV) of the assembly processes. The results show that the higher the CV, the total cost of all products assembled increased due to the complexity of balancing machine workload for a large number of products. Also, when the number of machines increased, given a constant number of products, the total cost of all products assembled increased because it is more difficult to keep the machines balanced. Similar results were obtained when a tighter imbalance factor was used.