A standards-based approach for linking as-planned to as-fabricated product data

Abstract

The digital thread links disparate systems across the product lifecycle to support data curation and information cultivation and enable data-driven applications, e.g., digital twin. Realizing the digital thread requires the integration of semantically-rich, open standards to facilitate the dynamic creation of context based on multiple viewpoints. This research develops such an approach to link as-planned (ISO 6983) to as-fabricated (MTConnect) product data using dynamic time warping. Applying this approach to a production part enabled the designer to make a more optimal decision from the perspective of the product lifecycle that would have otherwise been challenging to identify.

Introduction

Evolving industry challenges created by the increasingly distributed nature and growing complexity of modern manufacturing systems have driven the related concepts of Smart Manufacturing, Industry 4.0, and Cyber-Physical Production Systems [1]. The ultimate application of these concepts is a fully automated manufacturing system capable of flexibly producing lots of batch size one with little human interaction by measuring the current status of accessible capabilities [2], [3], [4]. Movement toward such applications has spurred the growth of standards and technologies that provide manufacturers with opportunities to leverage data to reduce cost, improve productivity, ensure first-pass success, and augment existing workforce capabilities [1].

The digital twin has been discussed as a key enabler of Smart Manufacturing, Industry 4.0, and Cyber-Physical Production Systems [2], [3], [4], [5], [6], [7]. For example, the Reference Architectural Model Industry 4.0 defines an “administration shell” (which is a digital twin) as the interface that digitizes a physical asset [8]. The digital twin is a digital representation of a physical asset that can be used to describe the asset’s properties, condition, and behavior through modeling, analysis, and simulation [2], [3], [4], [5], [6], [7]. Thus, a fully automated manufacturing system can collect data and information about its operation to update its digital twin to simulate the effects of any decision to be made [3]. Similarly, the digital twin has been proposed for production planning, scheduling, routing, and control [3], [4], [9]; design of digitized manufacturing systems [4]; management of geometric variation and digital geometric assurance [6], [7]; and design and operation of reconfigurable smart products [5]. Each of these applications relies on an underlying infrastructure to link data, information, and models from various systems across the product lifecycle to generate a holistic perspective of an asset; this infrastructure is the digital thread.

The digital thread links disparate systems across the product lifecycle and throughout the supply chain [10]. It supports data curation and information cultivation by linking data and information based on the context required for a specific use case. Hedberg et al. [10] describe a lifecycle information framework that explains how linked, contextualized, certified, and traceable data provided by the digital thread enables data-driven applications such as the digital twin. The challenge has been the inherent difficulty of aggregating and applying context to various types of data in different formats stored using different means in different locations [1], [10]. Helu et al. [1] proposed and implemented a reference architecture to integrate heterogeneous manufacturing systems for the digital thread. The goal of this paper is to build on this work by using the implemented reference architecture to develop a technical approach to link as-planned to as-executed product data that may be used for the digital twin and other data-driven applications of the digital thread.