To establish a coherent Digital Thread, encompassing diverse information obtained during the design process, it is imperative to ensure the traceability of information particularly between engineering and manufacturing teams. A challenge lies in maintaining links between data, particularly in the context of configuration management. Through the principles of complementarity, we explore links between the Engineering and the Manufacturing definitions through a major structural element. We forsee the principles of complementarity as a support for Digital Thread throughout the product lifecycle.

This paper conducts a systematic literature review about the management of rule-based product-portfolios with high variance. This type of portfolio is particularly distinctive in the chosen use case of the German automotive industry since it satisfies the requirements of mass customization and modularization. However, the research field of variant- and complexity management is manifold and multidimensional. This paper systematically searches the databases Scopus and Web of Science using the PRISMA method and briefly summarizes the main contributions and comparing them by elaborated topics.

In parallel with the industry 4.0 revolution, customers’ demand and number of product requirements are increasing, inducing increased product variability. System complexity is growing with the new technologies and system architectures. Hence, maintaining a system consistent and in the desired state becomes crucial. This paper tackles two problems: a product's variability and its temporal evolution. Regarding variability, Model Based Systems Engineering (MBSE) methods and Product Line Engineering (PLE) techniques become essential to configuring products by selecting and arranging features in a combination. In parallel, versioning and temporal evolution are managed with the configuration management (CM) principles. A versioned feature model (FM) is proposed. In PLE methodology, the first step is to model variability through traditional FM. This research presents an extension of the FM by integrating CM into it. The versioned FM includes not only features’ variants but also their versions, making it evolve in time. This work is presented as a base for a work that will study the application of CM for PLE. This study is done in an automotive industry context at Renault Group, and the model proposed is applied to Renault's systems.

Due to the complexity of financial products, consumers with low financial literacy are left behind. However, few practical studies investigated the impact of digital advisory systems to improve customer experience. Configuration systems, as the most popular expert systems, have never been applied as a financial tool. In this study, we explore the application of configuration systems to educate consumers in achieving their financial goals. The results highlight multiple benefits from using the configurator, including greater financial literacy and improved individual financial decision-making.

Manufacturing companies nowadays face growing numbers of heterogeneous customer requirements. Due to that, internal and external complexity lead to an increase in the associated costs. Especially companies with a high Engineer-to-Order business are strongly affected. To reduce external and internal complexity, Starting Solutions are a suitable way to do that. Starting Solutions require on the one hand the evaluation of product flexibility, on the other hand the evaluation of customer requirements. These two requirements are compared to each other and Starting Solutions are thereby derived.

With an increasing demand for product individualisation leading to increased product architecture complexity and -costs, modular kits are one common measure to cope with this issue. The management of such a modular kit as well as the methodical determination of a specific product variant is key to the manufacturer's success. As multiple influence factors need to be taken into account when configuring product variants, we propose a multi-dimensional geometric optimisation algorithm, allowing for prioritising varying customer demands and thereby determining the ideally balanced product variant.

Facing a rising competitive pressure, manufactures create advantages when they are able to offer customer-specific products to the conditions of a mass production article. Traditional configurators support the creation of personalized products from the elements of a modular product system, but are based on a pre-defined set of rules. The model based approach changes the environment of configuration from static configuration rules to the dependencies defined within the product's system model. So, by regarding target quantities of the user, the configurator identifies the optimal variant.

Today high quality and low product development turnaround time are company-wide priorities. Quality supporting processes such as an effective risk management system shall support continuous business running and meeting the goals of an organization. In this paper, an approach is presented on how to integrate the product risk management in Product Lifecycle Management for configured products by definition of an additional software module and its implementation.