Knowledge Transfer Quality Model Implementation - An Empirical Study in Product Engineering Contexts

Employee turnover, especially of experienced employees, is a constant challenge for companies as they are confronted with a loss of knowledge which they must compensate for. This leads to an accepted need to successfully transfer knowledge. Knowledge transfer has been reviewed in literature by multiple disciplines, whereas this paper focuses on a product engineering context. In this context, empirical research results show that knowledge transfer situations, e.g., communication of complex product specifications, can be improved regarding the speed of knowledge transfers by so-called interventions. Based on those findings, the quality of knowledge transfers is investigated further. Velocity-dependent, as well as quality-dependent interventions, are summarized in an intervention catalog. Whereas the effect of those velocity-dependent interventions has been investigated in empirical studies, the quality-dependent interventions have not yet been implemented in an industrial setting. This paper, therefore, describes the design and results of a workshop with experts from the area of knowledge management as well as from product development of universities and companies. The workshop was used to validate previously developed interventions and further add quality-dependent interventions. Further, the implementation of selected interventions in a product engineering context, using a Live-Lab as a research environment, is presented. The interventions intend to improve the quality of knowledge transfers in specific knowledge transfer situations. As this is validated by an empirical implementation study, the validity of this approach is justified

Analysis of Factors Influencing Knowledge Transfer between the Product and Production System Development as well as Production

The product development process is characterized by accelerating development cycles and increasing customer demands for a wide range of product variants. In addition, it is very knowledge-intensive and characterized by the reuse of knowledge in product generation engineering. Developing new products based on existing references, e.g. knowledge about design parameters or manufacturing technologies, requires effective and efficient transfer of knowledge. In a knowledge transfer, people of different domains, here product and production system development as well as production, make parts of their mental model tangible for others. When doing so, problems can occur that can cause information loss. Knowledge transfer has been reviewed in literature by multiple disciplines and defined differently amongst various understandings of its design. In this work, knowledge transfer includes the identification, transmission, and application of knowledge and thus addresses the problem of distributing knowledge within a company. To optimize knowledge transfer within the product engineering process to reduce information loss and knowledge deficits, factors that impact knowledge transfer must be considered. Therefore, this contribution examines factors that either influence the knowledge transfer positively or negatively, especially between product and production system development as well as production. In addition to a literature-based identification of influencing factors, a qualitative study interviewing experts in those fields enhances the findings. Furthermore, the collection of factors was assigned to four clusters: people, organization, technology, and knowledge and transfer. By linking the factors of each cluster, a model was created to be able to investigate the impact of changing factors within and between clusters providing a basis for closing knowledge deficits to enable effective and efficient knowledge transfer

Industrie 4.0 – An empirical and literature-based study how product development is influenced by the digital transformation

The fourth industrial revolution, referred to as Industrie 4.0 in the German high-tech strategy, is in most cases associated with the industrialization of production, but the term is increasingly broadly understood. Industrie 4.0 means the networking of all areas involved in the value creation process. In areas such as production and politics, visions are already being driven forward, but in the development of products and product-related services it is often unclear how engineering needs to change to realize the potentials of Industrie 4.0. Several research projects are already dealing with the development of new processes, methods and tools to enable these potentials. However, studies show that companies do not have the resources or strategies to implement such solutions. In many ways, the influence of Industrie 4.0 and its impact on product development is still insufficiently known. Therefore, a literature-based study was conducted to systematically identify context factors that characterize Industrie 4.0. In order to analyze the impact on product development, a second step involved an impact analysis with the context factors of Industrie 4.0 onto the context factors of product development known from the literature. In a third step, strongly influenced fields of product development were identified and their relevance for the realization of the potentials of Industrie 4.0 for product development was evaluated in an online survey. In addition, the current status in these fields was analyzed in interviews with experts from industry. With methods of foresight a portfolio was created, which couples the influence of Industrie 4.0 on the context factors of product development with their future robustness. Comparing the current state of development with the findings from the portfolio, recommendations for future research were formulated

Knowledge Transfer Quality Improvement - The Quality Enhancement of Knowledge Transfers in Product Engineering

Developing a new product generation requires the transfer of knowledge among various knowledge carriers. Several factors influence knowledge transfer, e.g., the complexity of engineering tasks or the competence of employees, which can decrease the efficiency and effectiveness of knowledge transfers in product engineering. Hence, improving those knowledge transfers obtains great potential, especially against the backdrop of experienced employees leaving the company due to retirement, so far, research results show, that the knowledge transfer velocity can be raised by following the Knowledge Transfer Velocity Model and implementing so-called interventions in a product engineering context. In most cases, the implemented interventions have a positive effect on knowledge transfer speed improvement. In addition to that, initial theoretical findings describe factors influencing the quality of knowledge transfers and outline a setting to empirically investigate how the quality can be improved by introducing a general description of knowledge transfer reference situations and principles to measure the quality of knowledge artifacts. To assess the quality of knowledge transfers in a product engineering context, the Knowledge Transfer Quality Model (KTQM) is created, which serves as a basis to develop and implement quality-dependent interventions for different knowledge transfer situations. As a result, this paper introduces the specifications of eight situation-adequate interventions to improve the quality of knowledge transfers in product engineering following an intervention template. Those interventions are intended to be implemented in an industrial setting to measure the quality of knowledge transfers and validate their effect

Vergleich von Produktinnovationsarten: Worin die Unterschiede wirklich begründet liegen

Seit jeher treibt die Motivation, erfolgreiche Produkte – Innovationen – am Markt zu vertreiben, die wirtschaftliche Produktentwicklung von Unternehmen an (Schumpeter 1912). Dabei sind neben einer erfolgreichen Einführung eines Produktes in den Markt, ein relevantes Produktprofil (Bedarfssituation am Markt) sowie die technische oder serviceseitige Lösung dieses Bedarfs durch eine Neuerung (Invention) notwendige Bestandteile einer Innovation (siehe Abbildung 1) (Albers et al. 2018a). Allerdings stellt das Kreieren einer Innovation kein triviales Unterfangen dar, sondern unterliegt vielmehr dem kontinuierlichen Umgang mit Unsicherheiten (Bennett & Lemoine 2014). Dies führt dazu, dass der Prozess in der Produktentwicklung nicht ausreichend planbar und infolgedessen äußerst störanfällig ist (Albers et al. 2019a). Um Entwicklerteams jedoch bestmöglich im Innovationsprozess durch geeignete Vorgehensweisen zu unterstützen, wurde eine Vielzahl an Prozessmodellen entwickelt (Wynn & Clarkson 2018). In der Literatur haben sich unterschiedliche Arten von Innovationen herauskristallisiert, die, insbesondere hinsichtlich der durch sie hervorgerufenen Marktveränderungen, unterschieden werden können (Disselkamp 2005). Diese Unterscheidung ist ausschließlich retrospektiv durchführbar. Zudem existiert keine systematische Betrachtung der Gemeinsamkeiten und Unterschiede zwischen den einzelnen Innovationsarten auf Basis der Informationen, die für die Entwicklung der Produkte notwendig sind. Im vorliegenden Beitrag erfolgt dieser Vergleich anhand dreier Beispiele mit jeweils drei Produkten. [... aus der Einleitung

Product-Production-CoDesign: An Approach on Integrated Product and Production Engineering Across Generations and Life Cycles

Shorter product life cycles and high product variance nowadays require efficient engineering of products and production systems. Hereby a further challenge is that costs over the entire life cycle of the product and production system are defined early in the process. Existing approaches in literature and practice such as simultaneous engineering and design for manufacturing incorporate aspects of production into product engineering. However, these approaches leave potential for increasing efficiency unused because knowledge from past generations of products, production systems, and business models is not stored and reused in a formalized way and future generations are not considered in the respective current engineering process. This article proposes an approach for integrated product and production engineering across generations and life cycles of products and production systems. This includes the consideration of related business models to successfully establish the products on the market as well as the anticipation of future product and production system characteristics. The presented approach can reduce both development and manufacturing costs as well as time to market and opens the vast technological potential for product design to achieve additional customer benefits. Three case studies elaborate on aspects of the proposed approach and present its benefits