The current business environment presents challenges for companies, including increased pressure on time to market, customer expectations, cost and increased competition. To overcome the challenges in the new business environment, the companies introduce common products components and variants in order to reduce complexity and improve the performance. Besides, the manufacturers attempt to increase the variety in products and services in response to the personalization demands; which leads to more complexity. However, the companies can improve the due-date setting and resource allocation to optimize internal process performance. This paper describes a design-time estimation model for planning engineering activities based on a quantification of the most important product complexity factors such as: 1) basic components variety, 2) functional requirements, 3) design interdependencies and 4) regulations and standards. Such factors can decrease or increase the expected time consumption for the specification tasks. This paper identifies key factors essential to assessing the expected hours for specific engineering tasks based on a case study and literature review. Qualitative and quantitative information was obtained by means of (i) archival documents, (ii) participant-observations, and (iii) workshops in the case company. These complexity factors are then combined to develop a mathematical design-time estimation model that supports the internal performance optimization in a given engineering design process. Finally, an IT tool is prototyped and tested in an engineering company. In conclusion, the developed model and IT tool assist the case company to improve the estimations for due-date setting and resource allocation to optimize internal process performance.
|Workshop||26th ISTE International Conference on Transdisciplinary Engineering|
|Period||29/07/2019 → 01/08/2019|
|Series||Advances in Transdisciplinary Engineering|
This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
- Design-time Estimation Model
- Complexity Management
- Quantifying Complexity
- Engineering Design