## 3 Results
### Literature Analysis
#### 3.1.2 Integrative Perspectives  
Focusing on material core products, integrative product-production perspectives [45] are established, bridging two academic communities as well as department boundaries in companies. The focus in the literature is set to production issues, such as land allocation, building, plant and production systems [34; 46]; the product lifecycle crosses the production or plant lifecycle in the production phase [33; 43; 47]. This is supported by intense studies on standardization of smart manufacturing (see Figure 3a [48]; cf. [49]). This perspective is taken up with regard to the Digital Twin [50] (cf. [51]): as a digital representation of the  
Figure 2: Specific perspectives of the product lifecycle: (**a**) intrinsic product lifecycle focusing on product development, production and use (based on [31]); (**b**) material lifecycle emphasizing volumes of material use in product lifecycle phases (see [36]); (**c**) software lifecycle illustration focusing on continuous evolution and resulting branches (based on [41]).  
current state of a physical product, it integrates data from development (digital master), production and use (digital shadow). It is also seen as an enabler for the integration of physical products and services. Even though services can be treated as products, a differentiation seems reasonable for the purpose of clarity. Hence, a product-service system consists of \"tangible products and intangible services designed and combined so that they jointly are capable of fulfilling specific customer needs\" [52] (cf. [53]). Both parts have to be considered with their specific lifecycles (see Figure 3b [54]). This approach can even be deepened when considering varying perspectives along the intrinsic product lifecycle: there are specific cycles in each phase (Figure 3c, highlights lifecycle data integration [55]).  
Again, several findings are deduced, which have to be considered with regard to the integration of perspectives.  
**Finding 5**.: _Lifecycle models need to be based on information circularity to utilize data science potentials and to enable knowledge management across cycles._  
Harmonization of terminologies is key to integrate data, models and processes. Integration is enabled by different methodologies in early phases (such as Integrated Product Development, Simultaneous and Concurrent Engineering). In these methodologies, lifecycle issues need to be incorporated. Consideration of different stakeholders is required, being responsible for or affected by different perspectives and phases.  
**Finding 6**.: _Realization is identified as the integrative phase, which (a) is to be prepared in engineering and (b) builds up the prerequisites for creating value._  
As soon as crossings are highlighted, models are often visualized using the chain metaphor instead of a circular representation. Integration is manifested in terms of product types, such as mechatronic products, cyber-physical systems and product-service systems. Thus, the view on integration as an intersection of perspectives is key for a comprehensive understanding of material and information flow when instantiating product instances from a product class. Therefore, the type of product characterizes the required lifecycle perspectives.  
**Finding 7**.: _When integrating perspectives, logical and temporal integration is required._  
While cycles are often idealized in a way that a new cycle starts after the End of Life (EoL) of an entire product class, new cycles are typically initiated in parallel to a preceding cycle (cf. technology 5-curves [56]). This view is often neglected by abstract lifecycle views.