<p>The capability of continuously producing good quality products with high productivity and low cost is critical for manufacturers. Generally, products are made up of components, which enable the product to perform its purpose. A complex product may be assembled from many components through multiple assembly stages. Any quality defects in a component may build up in the product. A good understanding of how the quality of components impacts the quality of products in a complex manufacturing system is essential for keeping the competitiveness of a manufacturer. </p> <p>In this research, a series of quality management models are proposed based on studying the relationship between component quality and product quality. Optimal quality control leads to increased competitiveness of a manufacturer, since it helps reduce cost, increase production, and limit environmental impact. The research starts from studying the tolerance allocation problem, which is fundamental of managing the tradeoff between quality, productivity, cost, and waste. First, a tolerance allocation method that minimizes cost is proposed. This model jointly considers process variation and tolerance specifications. The relation between manufacturer, user, design, and processing are embedded in the cost model. To solve the tolerance allocation problem from the root cause, i.e., the variations in production processes, a second tolerance allocation model is then provided. This model considers both product design (tolerance selection) and operation planning (or production rate selection). Relations among production rate, production cost, processing precision, and waste are considered. Furthermore, a new process control model that extends traditional statistical process control techniques is proposed. Data acquired from a manufacturing system are usually in the forms of time series, and anomalies in the time series are generally related to quality defects. A new method that can detect anomalies in time series data with long length and high dimensionality is developed. This model is based on recurrent neural networks, and the parameters of the neural networks can be trained using data acquired during routine operation of a manufacturing system. This is very beneficial because often, there are few data labeled as anomalies, since anomalies are hopefully rare events in a well-managed system. Last, quality control of remanufacturing is studied. A component-oriented reassembly model is proposed to manage the varied quality of returned component and varied needs of customers. In this model, returned components are inspected and assigned scores according to their quality/function, and categorized in a reassembly inventory. Based on the reassembly inventory, components are paired under the control of a reassembly strategy. A reassembly-score iteration algorithm is developed to identify the optimal reassembly strategy. The proposed model can reassemble products to meet a larger variety of customer needs, while simultaneously producing better remanufactured products.</p> In summary, this dissertation presents a series of novel quality management models to keep manufacturers’ competitiveness. These models are based on studying factors that impact component and product quality at multiple stages of a product life cycle. It was found that analyzing the relationship between component and product quality is a very effective way of improving product quality, saving cost, and reducing environmental impact of manufacturing.

Compared to other disciplines, software engineering as of today is still dependent on craftsmanship of highly-skilled workers. However, with constantly increasing complexity and efforts, existing software engineering approaches appear more and more inefficient. A paradigm shift towards industrial production methods seems inevitable. Recent advances in academia and practice have lead to the availability of industrial key principles in software development as well. Specialization is represented in software product lines, standardization and systematic reuse are available with component-based development, and automation has become accessible through model-driven engineering. While each of the above is well researched in theory, only few cases of successful implementation in the industry are known. This becomes even more evident in specialized areas of software engineering such as systems integration. Today’s IT systems need to quickly adapt to new business requirements due to mergers and acquisitions and cooperations between enterprises. This certainly leads to integration efforts, i.e. joining different subsystems into a cohesive whole in order to provide new functionality. In such an environment. the application of industrial methods for software development seems even more important. Unfortunately, software development in this field is a highly complex and heterogeneous undertaking, as IT environments differ from customer to customer. In such settings, existing industrialization concepts would never break even due to one-time projects and thus insufficient economies of scale and scope. This present thesis, therefore, describes a novel approach for a more efficient implementation of prior key principles while considering the characteristics of software development for systems integration. After identifying the characteristics of the field and their affects on currently-known industrialization concepts, an organizational model for industrialized systems integration has thus been developed. It takes software product lines and adapts them in a way feasible for a systems integrator active in several business domains. The result is a three-tiered model consolidating recurring activities and reducing the efforts for individual product lines. For the implementation of component-based development, the present thesis assesses current component approaches and applies an integration metamodel to the most suitable one. This ensures a common understanding of systems integration across different product lines and thus alleviates component reuse, even across product line boundaries. The approach is furthermore aligned with the organizational model to depict in which way component-based development may be applied in industrialized systems integration. Automating software development in systems integration with model-driven engineering was found to be insufficient in its current state. The reason herefore lies in insufficient tool chains and a lack of modelling standards. As an alternative, an XML-based configuration of products within a software product line has been developed. It models a product line and its products with the help of a domain-specific language and utilizes stylesheet transformations to generate compliable artefacts. The approach has been tested for its feasibility within an exemplarily implementation following a real-world scenario. As not all aspects of industrialized systems integration could be simulated in a laboratory environment, the concept was furthermore validated during several expert interviews with industry representatives. Here, it was also possible to assess cultural and economic aspects. The thesis concludes with a detailed summary of the contributions to the field and suggests further areas of research in the context of industrialized systems integration.