Kathrein, L., Meixner, K., Winkler, D., Lüder, A., & Biffl, S. (2019). Efficient Production System Resource Exploration Considering Product/ion Requirements. In 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) (pp. 665–672). IEEE. https://doi.org/10.1109/ETFA.2019.8869499
E194-01 - Forschungsbereich Information und Software Engineering
-
Published in:
2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)
-
Date (published):
2019
-
Event name:
24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2019)
-
Event date:
10-Sep-2019 - 13-Sep-2019
-
Event place:
Zaragoza, Spain
-
Number of Pages:
8
-
Publisher:
IEEE
-
Publisher:
IEEE
-
Peer reviewed:
Yes
-
Keywords:
Electrical and Electronic Engineering; Industrial and Manufacturing Engineering; Resource Selection; Product-Process-Resource; Manufacturing Knowledge; Catalogue Data
-
Abstract:
For the design of a Production System (PS), engineers have to select production resources that address the
associated product and production process, i.e., product/ion,
requirements. The dependencies between product, process, and
resource (PPR) provide the foundation for mapping properties
of the product and process to skills of production resources,
which may be represented as attributes in resource catalogue
tables. However, the production resources are represented in
resource catalogues by heterogeneous sets of attributes that make
it challenging to efficiently find a set of well-fitting resources. In
this paper, we present challenges and quality criteria that we
identified with domain experts at a large Production Systems
Engineering (PSE) company. We focus on use cases that explore
and select resources from large resource catalogues. We introduce
a data model to organize these resource catalogues in the solution
space based on PPR knowledge. We propose a method for
efficiently exploring the resource solution space regarding PPR
requirements. In a conceptual feasibility study, domain experts
rated the quality of the method based on a conceptual prototype.
The domain experts found the approach feasible and useful to
efficiently document decisions on resource selection.