Mikael Rosenqvist

Proactive assessment of basic complexity in manual assembly: development of a tool to predict and control operator-induced quality errors

A major challenge for manufacturing companies today is to manage a huge amount of product variants and build options at the same time in manufacturing engineering and in production. The overall complexity and risk of quality errors in manual assembly will increase placing high demands on the operators who must manage many different tasks in current production. Therefore, methods for decreasing and controlling assembly complexity are urgent because managing complex product and installation conditions will result in distinct competitive advantages. The objective of this paper is to present a method for predictive assessment of basic manual assembly complexity and explain how included complexity criteria were arrived at. The verified method includes 16 high complexity and 16 low complexity criteria to aid designers in preventing costly errors during assembly and create good basic assembly conditions in early design phases of new manufacturing concepts.

Operator Related Causes for Low Correlation Between Cat Simulations and Physical Results

The objective of this study was to explore correlation between CAT (Computer Aided Tolerancing) simulation and physically measured results in running production with focus on operator dependant factors. Therefore, the manual assembly of 25 different system solutions (locating scheme, tolerances, fasteners etc for a part) was analyzed. The study has been performed in the automotive industry and the system solutions are from 3 different cars in 2 different factories, all manual assembly in a paced line. The analysis shows several interesting results; in running production 33% of the measurements are not ok although 28% had their tolerance zone adjusted according to the measured results to make them ok. The conclusion is that the CAT simulations do not predict all the variation and therefore additional factors need to be included to enable accuracy improvement. Further relationships between additional factors such as operator influence and bad geometrical quality can be proven. A short term solution is suggested as well as a long term solution involving the need for development of additional functions in CAT tools, the overall goal being to decrease the difference between simulation results and actual physical results.

Robust design and geometry assurance considering assembly ergonomics

The objective of this study was to explore how assembly ergonomics issues were regarded by geometry engineers. Therefore, 21 geometry engineers in two manufacturing companies were interviewed. Their answers show good awareness of the implications of poor assembly ergonomics but appropriate working procedures and support in CAT (Computer Aided Tolerancing) tool are missing. 95% of the respondents would like to add consideration to assembly ergonomics in their CAT simulation. Based on this study a number of assembly factors that need to be included and considered in locating scheme definition and geometric stability analysis are identified and presented. Altogether, the results show a need for organizational change and CAT tool development.

Challenges Moving from Physical into Virtual Verification of Sheet Metal Assemblies

Within industry there is an established need for enhanced virtual tools and methods to improve product tolerance setting and conditions for successful manufacturing of non-rigid assemblies. A significant amount of research has been performed in the area, but there is still a need to find efficient working methods and the right preconditions in practice. This paper reports experiences and findings made during recently performed virtual matching and trimming of sheet metals in a real automotive industrial setting. A case is presented, demonstrating the possible use of the Computer Aided Tolerance(CAT) tool RD&T, (Robust Design & Tolerancing), in order to predict the geometric behavior of non-rigid parts when assembled. Scanned parts are used as input and the analysis is performed using the described virtual platform instead of physical type-bound rigging equipment traditionally used for conflict, gap and final springback analysis. The proposed working procedure, and the reasons behind it, are presented. The need of additional radical and incremental innovations is brought into light, in order to make earlier predictions in the product realization process. Furthermore, it is discussed whether the necessary changes in working procedures can impose innovation barriers in the future.