An Indicator-Based Process Monitoring Cockpit for Controlling and Enhancing Product Development Processes – An Industrial Case Study

Author(s):  
Thomas Luft ◽  
Simon Smoll ◽  
Sandro Wartzack
2020 ◽  
Vol 6 ◽  
Author(s):  
Ívar Örn Arnarsson ◽  
Emil Gustavsson ◽  
Mats Jirstrand ◽  
Johan Malmqvist

The problem at hand is that vast amount of data on industrial changes is captured and stored; yet the present challenge is to systematically retrieve and use them in a purposeful way. This paper presents an industrial case study where complex product development processes are modeled using the design structure matrix (DSM) to analyze engineering change requests sequences. Engineering change requests are documents used to initiate a change process to enhance a product. Due to the amount of changes made in different projects, engineers want to be able to analyze these change processes to identify patterns and propose the best practices. The previous work has not specifically explored modeling engineering change requests in a DSM to holistically analyze sequences. This case study analyzes engineering change request sequences from four recent industrial product development projects and compares patterns among them. In the end, this research can help to identify and guide process improvement work within projects.


Author(s):  
Paul Witherell ◽  
Sundar Krishnamurty ◽  
Ian Grosse ◽  
Jack Wileden

This paper introduces the development and application of semantic relatedness techniques towards improved knowledge management in product development processes through ontologies. As part of this work, several different semantic relatedness techniques are reviewed, including a meronomic technique recently introduced by the authors. An aggregate semantic relatedness measure, dubbed AIERO, is introduced to quantify underlying relationships between aspects of the product development process. To assess its applicability and accuracy, AIERO is tested using three separate, independently developed ontologies. The results indicate AIERO is capable of identifying and measuring relationships across a knowledge framework and can consistently produce results one would intuitively expect. Finally, a case study is presented to evaluate AIERO’s effectiveness in exposing underlying causal relationships across a product development platform. The results of this case study suggest that AIERO can uniquely quantify semantic relatedness between concepts, effectively enabling design engineers to systematically narrow the scope where causal relationships may exist between various domain concepts in the product development processes.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Viktoria Sundquist ◽  
Lisa Melander

Purpose This paper aims to investigate how various organizational interfaces between firms, units and functions, and the interplay between them, are developed and mobilized in product development processes. Design/methodology/approach The theoretical framework is based on the industrial network approach, including interactive resource development and the concept of organizational interfaces. A single case study is conducted at a world-leading industrial tool manufacturer, illustrating how resources are combined over time, crossing boundaries of firms, units and functions in the development of a hand-held digitalized tool for quality assurance in the production of cars. Data have been collected through semi-structured interviews, with additional data in the form of project reports, internal documents and practices for external collaboration. Findings In addition to inter-organizational interfaces, the study identifies a typology of scouting, embarking and integration interfaces at unit level (geographically spread units of one multinational corporation) and interpretation and reciprocal interfaces at function level. The conclusions show that these interfaces affect the outcome of three aspects of the product development process: product characteristics and functionality features, system integration and organizational network extent. Existing interfaces serve as a platform for developing interaction further and provide the interfaces with new content, thus moving between different types of interfaces. Product development processes also involve new interfaces where there was no previous interaction between the parties. Research limitations/implications This research has implications for the interplay between interfaces in cases involving multiple external and internal actors in resource combining efforts. Practical implications External interactions between firms influence and impact internal activities and resources. Managers need to be aware of the complex interdependencies between external and internal interfaces and resources. Managing organizational interfaces is about both exploiting established interfaces and developing new ones. Consequently, existing interfaces may be activated differently to align with new interaction purposes, which, in turn, requires efforts to combine resources according to the new conditions. Originality/value Previous research contains a typology of organizational interfaces between customers and suppliers. The study expands on this research by identifying internal interfaces between units and functions.


Author(s):  
Samuel Suss ◽  
Vincent Thomson

Product development processes of complex products are complex themselves and particularly difficult to plan and manage effectively. Although many organizations manage their product development processes by monitoring the status of documents that are created as deliverables, in fact the progress of the process is in large part based on the actual information flow which is required to develop the product and produce the documents. A vital element in making product development processes work well is the correct understanding of how information flows and how to facilitate its development. In this paper we describe an executable stochastic model of the product development process that incorporates the salient features of the interplay between the information development, exchange and progress of the technical work. Experiments with the model provide insight into the mechanisms that drive these complex processes.


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