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All in all, this master’s thesis aimed at making a theoretical and a practical contribution to improve the asset decision-making process at PPG. The theoretical contribution was to develop theory, which was achieved by designing an asset decision-making tool at PPG. The tool provided a second view on the LIIA in a different setting (in a low-cost and labor intensive industry). The thesis validated the usability of the LIIA method and presented possible improvements of the prioritization part of the LICAM method. Regarding the practical contribution it was aimed to support the operational organization of PPG’s Amsterdam factory in making more valuable decisions on their asset’s future. The tool identified strategic focus areas at the factory to prepare for future challenges. Moreover, an advice is given for a strategic roadmap of PPG’s Amsterdam factory. In order to do so, the developed support tool prioritizes lifetime impacts at PPG. Several challenges within asset management at PPG were identified by studying company documents. After the interviews with key stakeholder of the asset decision-making process it became visible that a good starting point for the development of the tool was to incorporate the lifetime impact identification analysis at PPG’s Amsterdam factory. Nevertheless, not all relevant challenges could be addressed by introducing the LIIA to the specific case of PPG. More literature was studied and the tool was extended based on MCDA to prioritize the identified lifetime impacts.

The developed tool was tested with the Amsterdam based expert team and the results were validated with the SBU Maintenance & Engineering department as well as with the Amsterdam plant management. Before the Amsterdam based expert team made use of the support tool there was no prioritization of lifetime impacts. They had an idea of the impacts affecting the factory in the future, but they did not know explicitly on which impacts to focus first. Consequently, the support tool makes the decision easier and provides the expert with a structured approach that can also be used to support his/her decision in front of senior management. In the end, it will also save the expert time as he/she will focus on the most important issues first. As the approach relies on expert knowledge it is possible to incorporate information form multidisciplinary perspectives. That ensures that no important lifetime impacts are overseen. When relying on expert knowledge there is always some subjectivity left in the results that cannot be completely mitigated. Nevertheless, expert knowledge collected in a discussion is a proven approach that generates valuable outcomes (i.e. see FMEA’s or the LIIA) and the model shows results that were in consistency with key stakeholders’ opinion (i.e. the SBU Maintenance and

Engineering Manager’s opinion). By accounting for conflicting criteria, the lifetime impacts collected in a multidisciplinary way all have an equal opportunity to be scored as highest priority. Therefore, it is essential that the model can deal with multiple conflicting criteria. In order to do so, the AHP method was introduced on the sub-criteria. AHP is able to deal with multiple conflicting criteria and scores the alternatives based on the weight assigned to the criteria. This is an important scientific contribution to improve the prioritization part of the LICAM. It thereby provides deeper insights into the exact impact score. Moreover, by aligning the BSC to PPG’s strategic objectives the impact score better reflects the strategic direction of the company and factory, and ultimately leads to better supported results. The visualization in the end contributed to better understanding of the results by the experts. It will help them to make better-supported decisions, and in making more specific decisions on individual criteria. Together with the SBU Maintenance and Engineering manager the results were verified, and it was decided that the support tool can also be used in a more generalized approach, for the 16 other European factories of PPG. One limitation of the application at the Amsterdam factory was the fact that there was no representative of the commercial perspective while prioritizing the lifetime impacts. Certainly, that could have changed the results slightly in favor of commercial lifetime impacts and should be kept in mind when designing business cases.

Generally, the tool helps the local team to expose important lifetime impacts in order to set the right priorities. The discussion during the expert sessions facilitated information sharing and knowledge exchange. Especially, the exchange of different views on lifetime impacts aided in a better understanding of the multidisciplinary focus perspectives of the experts. One specific strength of the model is that stakeholders are able to take time off their daily routine to be able to “break out” of daily fire-fighting. This was certainly one of the main advantages of the expert sessions, because measures to prepare better for the future can be initiated based on the results of the expert sessions. Moreover, the implemented tool supports a more structured ALCM at PPG. Even though the LIIA was originally designed for application at capital intensive industries, the adoption of this model at PPG showed that it can also be applied in more labor-intensive industries. Only the identified lifetime impacts vary slightly in those two cases. Whereas capital intensive industries, like the energy industry, have a stronger focus on reliability and uptime of machines, PPG’s lifetime impacts focused more on organizational matters, e.g. the shortage of skilled technicians. Another remark to the designed support tool is that it was originally designed to help to guide to more effective asset investments. Considering the technical lifetime impacts, the results can be used to introduce specific asset investment proposals, i.e. machines with more automation. However, the tool ended up not being restricted to asset investments but also incorporates strategic areas of the asset that call for improvement, named strategic focus areas. Strategic focus areas can also mean to improve the organization around the asset instead of making new investments. For example, by helping the local site team to design strategic objectives for the factory. One problem which was encountered during the interviews indicated that some local sites have trouble with creating a local vision for the factory. This can be viewed as an additional benefit of the tool. Thus, it can be stated that the developed model supports PPG in making more effective decisions regarding their assets and prepares their assets well for future challenges.