Big Data in Product Development: Need for a Data Strategy

Conception of a Digital Twin in Mechanical Engineering – A Case Study in Technical Product Development

“…If it is possible to feed use phase data from real life applications into the simulation models or utilise use phase data to validate simulation results against, more accurate simulation models can be built that lead to better products in the end. The term use phase data in this work is built on the definition of Wilberg et al (2017), where it refers to the data that is generated during the use phase by the product itself (e.g., by sensors or microprocessors) or by related services (e.g., Apps, maintenance reports, or repair reports). Such a coupling of simulation models and use phase data is often referred to as a Digital Twin.…”

Deriving a Use Phase Data Strategy for Connected Products: A Process Model

“…by sensors or microprocessors) and related product services (e.g. maintenance, repair, customer service, or mobile applications)" is called use phase data (Wilberg et al, 2017b). Use phase data can be very valuable for both internal (e.g., product development or service department) and external stakeholders (e.g., customers).…”

“…Connected products and services establish a connection between the manufacture and user that lasts until the end of the product's life (Porter and Heppelmann, 2015). Such data contains valuable insights about the behaviour of the customer and how the product and service are used (Wilberg et al, 2017b). Focusing on the customer allow for the development of market-tailored, and therefore competitive, products (Zhang and Fang, 2015).…”

“…They have a problem with adopting a data perspective and identifying use cases (Pols et al, 2016). Moreover, the complexity of the data and long product development processes in engineering companies make it necessary to plan ahead and define the required data points during the design phase (Köhler and Meir-Huber, 2014;Wilberg et al, 2017b). Different publications highlight the importance of structured planning that allows companies to identify suitable use cases, evaluate them, and plan their implementation (Davenport, 2014;Wirth and Wirth, 2017;Wilberg et al, 2017b).…”

“…Working with use phase data requires a clear plan to ensure that stakeholders collaborate whilst deriving and implementing use cases. However, a review of existing process models for data analytics initiatives revealed that they focus mostly on the processing and analysis of data, but not on the development of a use phase data strategy (Wilberg et al, 2017b). Many tools and algorithms for data analytics already exist, (Fayyad et al, 1996;Katal et al, 2013), but there is little support for the planning phase at the beginning.…”