# Process-Oriented Tolerance and Variation Management: Review and Classification
## 2 Method
### Classification Approach  
The objective of this paper is to enhance the accessibility of the field of PTVM and to provide a structured framework for its associated methods, models, and approaches. This should assist users of such models, as well as prospective researchers, in gaining an overview of the subject area and in identifying comparable or existing solutions more expeditiously for a particular application. In light of the aforementioned introduction, which highlighted the considerable diversity in the terminology and scope of the field, such an overview is particularly beneficial. In view of the extensive literature on this topic, it is necessary to further subdivide and classify the results of this review in order to improve clarity and to assist the reader, for example, in the selection of existing approaches. For this reason, the relevant researched publications are classified. A variety of distinguishing criteria may be employed for this purpose. In this context, it could be useful to distinguish between whether manufacturing or assembly processes are being considered, the methods and models applied, and the scope of consideration--i.e., whether a specific single process is examined in great detail or whether a process chain with its interactions is considered. In accordance with the authors\({}^{\dagger}\) view, the most significant similarities and differences in the application of methods and models can be identified in the consideration of single processes and process chains. Thus, this classification is employed in this publication. The primary difference in the application of individual methods and models is often whether specific parameters within a process and their effects on the process outcome are modeled, or whether the focus is on the interactions and variation propagation within a process chain. In addition, the user typically has a specific use case they wish to analyze. This may be a single process or multiple processes along a process chain. If the user wants to analyze and model specific process parameters of a single process in detail, it is helpful to have an overview of possible solutions that also focus on a single process in detail; interactions with preceding or subsequent processes are initially irrelevant. With this overview, they are now able to find existing solutions to their problem or possibly adopt similar solutions. If, for example, the classification was based on the models used, a use-case-specific overview of existing solutions would not be possible. In this case, the user would either have to examine all modeling approaches for a comparable use case or already have a precise understanding of which modeling approach is most appropriate. A purely binary distinction between manufacturing and assembly would obscure the overview of similar considerations, such as variation propagation through the fixture layouts and locator variations, which affect both assembly and manufacturing. In addition to approaches that focus on single processes or process chains, there are also approaches that are explicitly  
Figure 2: PRISMA flow diagram. suitable for considering both process chains and single processes, as well as approaches that focus on a higher-level perspective and consider PTVM more from an organizational point of view. Therefore, the classification consists of four classes: analysis of process chains, analysis of single processes, approaches for analyzing process chains and single processes, and overarching process-oriented tolerance management approaches. The class \"analysis of process chains\" always includes approaches that consider variations, tolerances, or influences along a complete process chain. A process chain refers to the sequence of multiple stations, between which a workpiece has to be handled, or to multiple self-contained processes, such as a milling process followed by a drilling process. The focus is on examining the relationships between the processes, while the modeling of the single processes is of secondary importance.