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Variability Modeling of Products, Processes, and Resources in Cyber-Physical Production Systems Engineering

Kristof Meixner, Kevin Feichtinger, Hafiyyan Sayyid Fadhlillah, Sandra Greiner, Hannes Marcher, Rick Rabiser, Stefan Biffl

Abstract

Cyber-Physical Production Systems (CPPSs), such as automated car manufacturing plants, execute a configurable sequence of production steps to manufacture products from a product portfolio. In CPPS engineering, domain experts start with manually determining feasible production step sequences and resources based on implicit knowledge. This process is hard to reproduce and highly inefficient. In this paper, we present the Extended Iterative Process Sequence Exploration (eIPSE) approach to derive variability models for products, processes, and resources from a domain-specific description. To automate the integrated exploration and configuration process for a CPPS, we provide a toolchain which automatically reduces the configuration space and allows to generate CPPS artifacts, such as control code for resources. We evaluate the approach with four real-world use cases, including the generation of control code artifacts, and an observational user study to collect feedback from engineers with different backgrounds. The results confirm the usefulness of the eIPSE approach and accompanying prototype to straightforwardly configure a desired CPPS.

Variability Modeling of Products, Processes, and Resources in Cyber-Physical Production Systems Engineering

Abstract

Cyber-Physical Production Systems (CPPSs), such as automated car manufacturing plants, execute a configurable sequence of production steps to manufacture products from a product portfolio. In CPPS engineering, domain experts start with manually determining feasible production step sequences and resources based on implicit knowledge. This process is hard to reproduce and highly inefficient. In this paper, we present the Extended Iterative Process Sequence Exploration (eIPSE) approach to derive variability models for products, processes, and resources from a domain-specific description. To automate the integrated exploration and configuration process for a CPPS, we provide a toolchain which automatically reduces the configuration space and allows to generate CPPS artifacts, such as control code for resources. We evaluate the approach with four real-world use cases, including the generation of control code artifacts, and an observational user study to collect feedback from engineers with different backgrounds. The results confirm the usefulness of the eIPSE approach and accompanying prototype to straightforwardly configure a desired CPPS.
Paper Structure (67 sections, 1 equation, 10 figures, 8 tables)

This paper contains 67 sections, 1 equation, 10 figures, 8 tables.

Table of Contents

  1. Introduction
  2. Background
  3. CPPS Engineering
  4. Variability Modeling
  5. Motivating Case Study
  6. Methodology
  7. Adopting Variability Modeling for CPPS Process Exploration and Configuration
  8. Requirements for eIPSE
  9. The Extended IPSE Approach
  10. Overview
  11. Details
  12. Summary
  13. Toolchain Architecture
  14. environment.
  15. TRAVART environment.
  16. ...and 52 more sections

Figures (10)

  • Figure 1: FeatureIDE FeatureIDE of product (top) and production resource (bottom) variability of the shift fork case study.
  • Figure 2: Excerpt of a model for the production steps of a shift fork in VDI 3682 notation vdi_3682.
  • Figure 3: Design Science methodology hevner2007threehevner2008design for this work.
  • Figure 4: (Human & automated) process steps for exploring production process steps based on a product configuration (updated steps have solid contours, novel steps, additionally a darker color).
  • Figure 5: Architecture of the toolchain in UML component diagram notation (novel and updated components are depicted with solid contours).
  • ...and 5 more figures