Abstract
Product development companies collect data in form of Engineering Change Requests for logged design issues, tests, and product iterations. These documents are rich in unstructured data (e.g. free text). Previous research affirms that product developers find that current IT systems lack capabilities to accurately retrieve relevant documents with unstructured data. In this research, we demonstrate a method using Natural Language Processing and document clustering algorithms to find structurally or contextually related documents from databases containing Engineering Change Request documents. The aim is to radically decrease the time needed to effectively search for related engineering documents, organize search results, and create labeled clusters from these documents by utilizing Natural Language Processing algorithms. A domain knowledge expert at the case company evaluated the results and confirmed that the algorithms we applied managed to find relevant document clusters given the queries tested.
Highlights
A product development (PD) project is a complex network of designs and design changes in which design attributes often have dependencies
We addressed two research questions: 1. Can Natural Language Processing (NLP) and document clustering algorithms be utilized for grouping Engineering Change Requests (ECRs)?
The labels were generated by the document clustering algorithm (i.e. Latent Dirichlet Allocation (LDA)) and should summarize the main key words connected to the clusters
Summary
A product development (PD) project is a complex network of designs and design changes in which design attributes often have dependencies. Product developers often need to make changes to previous designs to improve, enhance, or adapt a product to identified opportunities. Considering the pervasive trend of shorter development lead times, Prasad (2016b) argues that the search and re-use ‘‘information latency’’ needs to be brought down from days to minutes or even seconds, requiring more broadly applicable and faster information search tools. The design will during the development process evolve through a multitude of iterations, based on knowledge gained from simulations and tests, carried out within the current project as well as from other projects that a company is running in parallel. To efficiently iterate a design is a key capability in an interconnected concurrent engineering process (Prasad, 2016a)
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