The semiconductor manufacturing process is a complex process that can consist of hundreds if not thousands of steps. During this process an enormous amount of data is generated and collected by several different systems. Analyzing this data can be complicated and time consuming. But, in order to optimize the manufacturing process, it is important to be able to process data quickly and provide data consumers an easy, meaningful way to view the data. Data consumers at a management level need to view data differently than someone who works in the semiconductor fabrication plant (FAB) operating the manufacturing equipment or a maintenance technician who fixes and maintains the equipment. So, it is important to provide these different data views to the users in a logical, organized way. This paper will discuss what a dashboard is, an overview of the semiconductor manufacturing process, and one implementation of a dashboard for the semiconductor industry, the Semiconductor Manufacturing Dashboard (SMD). An explanation of the systems involved in collecting and loading the data, the database structures, and the web servers used for development and production will also be discussed. / text

published_or_final_version / Industrial and Manufacturing Systems Engineering / Master / Master of Philosophy

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The need to increase productivity, improve quality and increase flexibility whist continuously reducing costs is driving manufacturers to search for alternative means of converting the product idea into a manufactured product. Plant automation systems which are the nervous system and increasingly the intelligence of the plant have an integral role to play in this regard. This study investigates the convergence between traditional IT and Industrial Automation with a view to understanding how this phenomenon will affect operational excellence within the manufacturing environment. The study further investigates the key determinants of success for automation systems within the broader business context and how this can lead to an advantage over competitors. The study is limited to manufacturing operations within the greater Durban area. The results revealed that there is a clear relationship between industrial automation and information technology in manufacturing organisations. However, of interest is the fact that in the majority of the organisations surveyed the two functions operate as separate entities within the organisation resulting in overlaps of responsibility and accountability for key equipment and processes. Factory efficiency was found to be the key determinant of success in the majority of the organisations surveyed whilst the provisioning of production data when used strategically was found to have a positive effect in allowing the organisation to gain an advantage over its competitors. Due to the limitation of the short time frame allocated to this research, the study could not go in detail into the drivers of these findings consequently recommendations for further research is made. / Thesis (MBA)-University of KwaZulu-Natal, 2007.

The evolution of the manufacturing industry may be viewed as proceeding from Dedicated Manufacturing Systems (DMS) to Reconfigurable Manufacturing Systems (RMS). Customer requirements change unpredictably, and so DMS are no longer able to meet modern manufacturing requirements. RMS are designed with the focus of providing rapid response to a change in product design, within specified part families. The movement from DMS to RMS facilitates mass-production of custom products. Custom parts require inspection routines that can facilitate variations in product parameters such as dimensions, shape, and throughputs. Quality control and part inspection are key processes in the lifecycle of a product. These processes are able to verify product quality; and can provide essential feedback for enhancing other processes. Mass-producing custom parts requires more complex and frequent quality control and inspection routines, than were implemented previously. Complex, and higher frequencies of inspection negatively impact inspection times, and inherently, production rates. For manufacturers to successfully mass-produce custom parts, processes which can perform complex and varying quality control operations need to be employed. Furthermore, such processes should perform inspections without significantly impacting production rates. A method of reducing the impact of high frequency inspection of customized parts on production rates is needed. This dissertation focuses on the research, design, construction, assembly, and testing of a Non- Contact Automated Inspection System (NCAIS). The NCAIS was focused on performing quality control operations whilst maintaining the maximum production rate of a particular Computer Integrated Manufacturing (CIM) cell. The CIM cell formed part of a research project in the School of Mechanical Engineering, University of KwaZulu-Natal; and was used to simulate mass-production of custom parts. Two methods of maintaining the maximum production rate were explored. The first method was the automated visual inspection of moving custom parts. The second method was to inspect only specified Regions of Interest (ROIs). Mechatronic engineering principles were used to integrate sensor articulation, image acquisition, and image processing systems. A specified maximum production rate was maintained during inspection, without stoppage of parts along the production line occurring. The results obtained may be expanded to specific manufacturing industries. / Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2009.

Large Area Maskless Photopolymerization (LAMP) is a novel additive manufacturing technology currently being developed at Georgia Tech in collaboration with the University of Michigan at Ann Arbor and PCC Airfoils. It is intended for the fabrication of integrally cored ceramic molds for the investment casting of precision components such as high-pressure turbine blades. This dissertation addresses the digital data processing and computational design needs for this technology. Several data processing schemes like direct slicing, STL slicing, post-processing schemes like error checking, part placement and tiling etc. were developed in order to enable the basic functionality of the LAMP process. A detailed overview of these schemes and their implementation details are given in this dissertation. Several computational schemes to improve the quality and accuracy of parts produced through the LAMP process were also implemented. These include a novel volume deviation based adaptive slicing method to adaptively slice native CAD models, a gray scaling and dithering approach to reduce stair stepping effect on downward facing surfaces and a preliminary experimental study to characterize the side curing behavior of the LAMP photo-curable suspension for pre-build image compensation. The implementation details and a discussion of the results obtained using these schemes are given. A novel approach for addressing the “floating island” problem encountered in additive manufacturing was also developed. The need for supports specific to the kind of parts being built through LAMP is evaluated and a support generation strategy different from the previously reported approaches in the literature is presented. Finally, a few novel film cooling schemes that are extremely challenging to fabricate using existing manufacturing technologies but possible to fabricate using LAMP are chosen and analyzed for their cooling performance. It is shown that such novel schemes perform much better in cooling the blade surface than the conventionally implemented schemes and hence this final component of work gives a better appreciation of the impact LAMP technology has in disrupting the state of the art in turbine blade manufacturing and truly taking the blade designs to the next level.

This thesis deals with development of lean and green production systems from an action research point of view. The studies focus on Swedish-based automotive and vehicle industries and their aims to integrate sustainable thinking and environmental care into their operations management. Starting from operations management in manufacturing and corporate sustainable development, the research is built on how to integrate these two views into one production system. The systematic structure of a multiple-target improvement process with methodologies and tools designed to achieve the sustainability vision has been studied. Since lean as well as green production is based on the entire value chain, the research has gone beyond legal company limits and included the collaborative efforts between suppliers and customers in the value chain. The thesis includes six papers and describes approaches on how to implement integration, how to structure and integrate improvement management systems, how to set up an integrated monitoring and control system for the business and how to organise and redesign green lean tools and methodologies to support collaboration towards common targets. The results can be used for exploration and hypothesis formulation for further studies and development of integrated production systems and collaboration systems. The thesis helps answering how to integrate and implement company-specific green lean production systems.

This research project analysed the characteristics of SMMEs in general, and suggests that collaborative manufacturing (CM) provides a means to both overcome the weaknesses and explore the strengths of SMMEs. / Thesis (PhD)--University of South Australia, 2008.