Delta modeling for variant-rich and evolving manufacturing systems

Abstract

Manufacturing systems exist in many different variants and evolve over time in order to meet changing requirements or environment contexts. This leads to an increased design complexity as well as to increased maintenance effort. In order to appropriately handle this inherent complexity, we propose a multi-perspective modeling approach combining UML activity, component-based and state chart diagrams to separately represent different system aspects. We combine the multi-perspective modeling approach with delta modeling to capture the variability and evolution of these manufacturing systems. Delta modeling allows a flexible, yet concise and understandable representation of variability in a modular manner. We examine our approach by applying it to a manufacturing lab demonstrator system with automated code generation from models obtained by delta application.

Evolution of software in automated production systems: Challenges and research directions

“…Deltas encapsulate all necessary changes to get from one variant, which is, e.g., the most basic variant, to an arbitrary variant in the product line. Delta modeling has so far been applied to represent variability of software architectures (Haber et al, 2011), Java programs (Schaefer, 2010) and a multi-perspective modeling approach for manufacturing systems (Kowal et al, 2014). Each perspective consists of a different UML diagram on which deltas can be applied making variability on all abstraction levels of the system manageable.…”

“…Variants and versions are managed in the same manner by delta modeling. Therefore, the multi-perspective modeling approach in Kowal et al (2014) is also applicable for evolution (cp. Section 7.2).…”

Towards interdisciplinary variability modeling for automated production systems: Opportunities and challenges when applying delta modeling: A case study

“…A variant for a particular system configuration is generated by applying a set of deltas to the core product. DM has so far been applied to represent static variability of software architectures [31], Java programs [32] and different UML models used to model a manufacturing system [33]. CVL and DM are both language-independent and very powerful variability modeling concepts.…”

“…3b. Examples on how DM is applied for behavioral models are given, e.g., in [37,38] for MATLAB/Simulink models and in [33] for UML state charts. These findings can be applied for further behavioral models, e.g., arbitrary state machines as necessary for our stream processing functions.…”

A Structural Prototype for Planning and Controlling a Manufacturing System

“…To structure the information and knowledge needed for a manufacturing system, the object-oriented technologies has been widely used in automated manufacturing models [7], process planning, manufacturing activities and resources [8] [9], as well as Petri nets for planning and controlling manufacturing activities [10]. The integration of several models is usually made for efficient manufacturing systems.…”