Frugal innovation, an innovation philosophy encapsulating a significant reduction of costs and focus on core functionality of products is used by companies across the globe to reach expanded markets. Nevertheless, manufacturing processes seem to have largely been excluded from frugal innovation applications. Reconfigurable manufacturing systems offer large opportunities for increasing both the efficiency and flexibility of production systems yet have not considered manufacturing sustainability or resource-constraints. The combination of frugal and reconfigurable manufacturing into frugal, reconfigurable manufacturing systems (F-RMSs) therefore inherently offers opportunities to make frugal manufacturing viable and RMSs less wasteful. F-RMSs are explored in this paper. The opportunities inherent in their combination are explored, the exact meaning of F-RMSs delineated and criteria for its success defined. A list of core characteristics and enablers is also defined to further distinguish the F-RMS as a manufacturing system. As such the F-RMS is fully conceptualized. Subsequently, a design framework for F-RMSs is defined based on this definition and criteria. In this way F-RMS design is facilitated and its eventual implementation enabled. The framework is focused on a requirements gathering and basic design step, where advanced design and implementation guidelines are defined on a case-by-case basis. The thesis is finalized with a set of case studies where the framework is carried out at different companies to (re)design an F-RMS. The functioning of the F-RMS is thereby validated, with the opportunities inherent in their combination recognized in the practical designs created.

Semiconductor product development becomes increasingly challenging due to diminishing product life cycles, miniaturization, introduction of new physical principles, and new manufacturing processes. These problems are compounded in the absence of standardized development processes for the most complex semiconductor products like MEMS technologies, because the manufacturing of these products is often outsourced. Suppliers play a pivoting role in the realization of the product, from product design until process design and ramp-up. The supplier selection problem in this industry denotes the challenges in finding the right supplier while meeting all the technical, process and business requirements. The contribution of this research is in presenting how to develop a generic methodology for data-driven co-development. Thereby, this work presents a novel product development framework that leverages co-development and supply chain integration through data-driven decision-making. Co-development is reached through standardized methods for generating the required engineering output for supplier selection. Supply chain integration is introduced in the early stages of product development. This synthesizes with the outsourced manufacturing processes. Clustering algorithms are used to effectively shortlist suppliers based on their competences, and provide insights into supplier profiles and gaps. The latter is used to draw strategies for developing unattainable technologies. Using the framework, the required engineering output for supplier selection was generated in 77% less time while reducing information asymmetries between actors in the product development process. Furthermore, the framework made it possible to quantify decisions, allowed for supplier profile recognition and gap identification through its hybrid automated approach, and supplier shortlisting in 95% less time. This efficiency does not only showcase the immediate benefits of the proposed methodology, but also lays the foundation for future research towards a fully automated approach in semiconductor product development. The developed framework includes information flows between actors and steps in the product development process, their interfaces and demonstrates its added value and potential for a fully automated yet efficient future approach in semiconductor product development.

This research investigates the application of a digital twin in managing challenges of variability and complexity within systems by using a case study at KLM Engineering & Maintenance. Using the DMADV (define, measure, analyse, design and verify) methodology, the research evaluates the problem using a literature review, measures and analyses the current state of the Logistic Handling Area (LHA), designs a digital twin concept and verifies its value. The literature review highlights the variability in the Maintenance, Repair and Overhaul (MRO) industry, which enables the investigation of digital twin applications for dynamic coordination. The analysis phase reveals significant operational challenges arising from variability in inflows and processing times, enhanced by system complexity and integral coordination issues between departments. To address these challenges, a digital twin is designed that enables real-time monitoring of KPIs, testing of dynamic resource allocation and integral operational target setting. The value assessment shows that the digital twin can support process operators by managing variability through continuous monitoring and evaluation of resource allocation, ultimately achieving predictable and stable system performance in a complex and variable environment.

Amsterdam Airport Schiphol (AAS) faces operational challenges from fluctuating baggage volumes and limited infrastructure, necessitating innovative approaches to optimize baggage handling. This study focuses on strategic buffering of super cold transfer baggage to reduce peak occupancy at transfer infeed points. A simulation model, integrated with TBATS forecasting, evaluates three buffering strategies (fixed target, polynomial, hybrid) and two reintroduction strategies (early, optimized release) under normal, disrupted, and highdemand scenarios. The results demonstrate peak occupancy reductions of up to 26.8%, with the polynomial buffering strategy and optimized release proving the most effective, though requiring additional AGV resources. Fixed target strategies offer a more resource-efficient alternative while maintaining substantial improvements in peak shaving. Early release strategies further reduce buffer congestion, optimizing operations for space-constrained environments. This research provides actionable insights for AAS and similar airports, highlighting trade-offs between efficiency, resource requirements, and operational constraints. The findings contribute to scalable solutions for managing growing baggage volumes within existing infrastructure, enhancing system resilience and performance.

Quality control is considered an important process in manufacturing to minimise waste related to the manufacturing process. A way of performing quality control is with help of machine vision. Understanding all decisions that are to be made when designing a machine vision system for quality control is essential, but challenging. This research presents a method that aids decision-makers in the process of designing these machine vision systems for quality control so the efficiency of the decision-making process can be increased. The method results in a knowledge base and a tool that can both be considered as useful to decision-makers. The method was designed by following a Design Science Research approach and the method was applied on a use case in the automotive industry to prove that it addresses its goal.

The present study was designed to gain a deeper understanding of RTI control and Supply Chain Coordination, with a specific focus on the practical challenges experienced in the reverse logistics by asset-owner and asset-users. A case study at EPS - an RTI owner - is performed and a practical problem has been addressed with a design science and TIL systems engineering approach. It was observed that a huge amount of deposit is allocated to a retailer's generic account. The current state analysis found that this problem is mainly due to inefficiency in the current identification process with physical SSCC labels. The design goal of minimising the "Delta" -the number of unidentifiable return packages- was defined. Ways to redesign the reverse logistics were determined with the aim that all return packages can be allocated to the retailer at shop level. Based on the future state requirements and the design goal, the concept of matchmaking is developed as a way to achieve the design goal. This thesis shows that a matchmaking system can improve the traceability of return packages and that it has the potential in bringing the Delta of return packages with missing shoplink to zero.
The matchmaking system is defined as the framework that ensures matchmaking, which uses a "key" generated by the sender to represent the return package. If the receiver can find the key upon arrival of the return package at the depot, the sender can be identified. Seven matchmaking systems were considered. Five alternatives use unique tray identities as key. One alternative uses the load carrier as key and the last alternative uses the return package identity as key. The validation results show that an "all read" or "reading of all individual trays" is not a requisite for a working matchmaking system. By contrast, as long as a certain ratio of reading at two locations is reached, an all-read scenario can be mimicked. The assessment investigated the instances in which zero mismatch take place. Results show that the higher the data capture capability of both the sender and receiver, the higher the chance a match can take place and the smaller the chance of a mismatch. This thesis creates insights on requirements for enhancing traceability of RTI's in the return chain and developed a matchmaking concept that can address the practical problem of returns without traceability of shop origin. The developed matchmaking concept is the outcome of an analysis of the current state and makes use of data elements that are already being collected in the database, in the case of EPS. The study addresses how collected data can be leveraged for enhanced RTI management in the reverse logistics and may inspire practitioners to face challenges with a similar lean approach.

This research aim was to design a centralised model that redefines definitions, standardises maintenance by categorisation, and reduces waste by introducing new slot lengths, leading to an equilibrium between flights and maintenance. This equilibrium enhances the airline’s capacity to manage maintenance efficiently and ensures greater uptime. The model addresses the important aspects of airline planning, including maintenance, flight and operation planning. Lean Six Sigma theories serve as a framework to combine the different plannings. The key importance is that the model considers all the stakeholders instead of only one so that the equilibrium between excessive flying and excessive maintenance can be established. In striking such a balance, uptime is assumed to increase.