## 5 Developing the Approach for the Assessment of Innovation Projects in Manufacturing
### Phase I: Criteria Derivation for Innovation Project Assessment in Manufacturing
Lastly, the final verification of the criteria catalog was carried out in a workshop with eight researchers from a German research institute for production technology. During the half-day workshop, a three-step approach was conducted. First, the criteria catalog was presented and discussed within the group regarding completeness. Second, the group was challenged to use the catalog to  
Figure 3: Overview of the methodological derivation of the criteria and schematic structure of the criteria catalog for innovation project assessment. describe their recent research projects to test the practical applicability of the catalog. Third, the workshop results were summarized by creating the final criteria catalog and made available to the participants. After completing this structured approach, 11 criteria groups emerged, containing 34 sub-criteria groups with 123 detailed criteria. The final catalog is detailed in the following figures (Figures 4-6). Figure 4: Relevant criteria to assess the potential of an innovation project in manufacturing. The first main criteria group (Potential) describes what relevant changes can be expected after the implementation of an innovation project. The relevant outcomes are derived from the generic target dimensions of manufacturing described by [PERSON] et al. [31] and include costs, quality, time, changeability, social, ecological, and strategic factors. Cost represents the first main criterion within the potentials, as cost reduction is the main contribution of manufacturing to secure a company's profitability. The cost-specific evaluation of an innovation project focuses exclusively on the long-term effects on the cost structure of the company since one-off costs are considered in the effort evaluation. The further structuring of costs is based on the process-related cost analysis in manufacturing according to [PERSON] and [PERSON] [71]. With reference to the scope, organization, production, logistics, and quality (customers), processes are further detailed in the sub-criteria. In addition, the perspective on manufacturing factors according to [PERSON] [72] was used in the catalog. Following this, all costs of manufacturing factors, such as personnel or material, can be attributed to the respective activities within the detailed criteria. Subsequently, the cost-relevant criteria were detailed as displayed in Figure 4 with the help of the relevant preliminary work [73, 74, 75, 52, 71, 72, 73, 74, 75]. Figure 5: Relevant criteria to assess the efforts of innovation projects in manufacturing. Quality is the second main criterion of the potential assessment. Generally, quality in manufacturing is divided into an internal and an external perspective. Internally, process quality is defined by error-free and efficient processes. From an external customer perspective, product quality is the decisive factor. Therefore, it is necessary to identify characteristics for both perspectives to assess the project-related effects. To describe process quality in manufacturing, four general sub-objectives and characteristics were identified based on the scientific literature [53; 54; 55; 56]. Effects on product quality are indirect, e.g., a better surface quality due to a new manufacturing process. As products are diverse, a generic definition of quality characteristics is not possible. Consequently, the quality characteristics are to be detailed by the user. The complete detailing of the criterion can be found in Figure 4.  
The third main criterion is time. There is a common understanding in the literature that a short lead time is one of the main objectives in manufacturing. It describes how long a product needs to pass through the entire manufacturing process. Accordingly, the effects of project-related changes on the lead time are to be evaluated. Therefore, the internal manufacturing lead time was broken down into waiting, transport, and processing, as well as planned and unplanned downtime [57; 76]. Further detail is displayed in Figure 4 above.