Identifying Product Defects by Utilizing Component Non-conformity Data
Ylivainio, Esa (2016)
Ylivainio, Esa
Metropolia Ammattikorkeakoulu
2016
All rights reserved
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2016061713161
https://urn.fi/URN:NBN:fi:amk-2016061713161
Tiivistelmä
This Thesis focuses on identifying product defects in an industrial product consisting of thousands of individual components. An industrial product with a lifetime of several decades may involve intense maintenance operations and, as a result, there are multiple warranty and post-warranty periods scattered along the product lifetime. Hence, design errors require to be screened from many sources of data in order to be able to systematically act on issues causing impacts to the end user. To be able to act systematically, two types of sources are required to build an improvement business case, first, the quantitative sources to know which cases require attention and, second, the qualitative sources to know how the issue could be fixed. Currently, the case company is lacking the quantitative sources which cause incomplete business cases and possibly some issues being missed.
The objective of this Thesis is to propose improvements for the current screening processes when identifying product defects. The proposal is to include the sources with valuable information of performance failures when components do not meet customer expectations, regardless of the warranty status of a product or a component. The study is conducted as a case study and start by analyzing the case company current processes related to non-conformity screening. When issues with the current processes are identified, findings from best practice of reliability follow-up are combined with stakeholder ideas to create proposals for improvements.
The output of this Thesis is the proposal to improve the coverage of quantitative statistical data for identifying product defects collected from non-conformity cases.
The case company can benefit of the Thesis by aligning quantitative data sources to better match the already established qualitative sources of data in order to create solid business cases for the product improvement process. In addition, new data sources may be able to raise awareness of issues which may have previously remained undetected.
The objective of this Thesis is to propose improvements for the current screening processes when identifying product defects. The proposal is to include the sources with valuable information of performance failures when components do not meet customer expectations, regardless of the warranty status of a product or a component. The study is conducted as a case study and start by analyzing the case company current processes related to non-conformity screening. When issues with the current processes are identified, findings from best practice of reliability follow-up are combined with stakeholder ideas to create proposals for improvements.
The output of this Thesis is the proposal to improve the coverage of quantitative statistical data for identifying product defects collected from non-conformity cases.
The case company can benefit of the Thesis by aligning quantitative data sources to better match the already established qualitative sources of data in order to create solid business cases for the product improvement process. In addition, new data sources may be able to raise awareness of issues which may have previously remained undetected.