Evolution of production facilities and its impact on non-functional requirements

Abstract

Due to high acquisition costs, production facilities are to operate for many years or even decades to be profitable. During operation, application and customer requirements change rather frequently. Therefore, a process operator must constantly evolve the control software and the underlying system. This task is restricted by specific constraints in the domain of production systems (e.g. short reaction times, high dependency on physics, etc.) hindering the proper use of formal engineering processes, which results in a lack of explicit documentation. Under such circumstances, it is evident that long-living automation software systems require special strategies to deal with incomplete information. Moreover, due to the complexity of production plants, the interconnection between evolution scenarios and system requirements might be complex. Then, a link between evolution and fulfillment of requirements is to be defined. In an effort to give a structured overview of the resulting difficulties due to improperly performed evolution steps in production facilities, this contribution presents a categorization of evolution scenarios from a practical point of view. In addition, interrelations between physical process measurements and highlevel requirements are shown. This paper aims at describing the occurring difficulties within evolving production systems from a practical point of view and establishing a first step towards exploiting process measurements for requirement-aware production systems.

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

“…they are unique systems, which are designed and implemented once a customer has awarded a contract to an aPS supplier (Birkhofer et al, 2010). Referring to Table 1 Categories of evolution scenarios based on a refinement of Ladiges et al (2013) with references to PPU case study examples in Section 2.2 ( * ) (Vogel-Heuser et al, 2014d) and (#) (Vogel-Heuser et al, 2014c). This evolution scenario category is referred to as "Ia" henceforth, its main characteristics are shown in column "Ia" of Table 1.…”

“…Managing (evolving) functional requirements is a well-studied topic in the literature (Ramesh and Jarke, 2001). In contrast, managing nonfunctional requirements -especially dependability requirementsfor aPS is rarely addressed Ladiges et al, 2013). One reason is that the relationship between evolution and dependability of a system is vaguely understood until now because both are very complex challenges (Felici, 2003;Machado et al, 2006;Vogel-Heuser et al, 2014c).…”

Design for future: managed software evolution

“…The evolution of the mechanical, electrical and software parts of the PPU over the last ten years is structured into 16 scenarios. Besides functionally driven evolution, i.e., processing of other types of work pieces (colour, material), also quality requirements [9], e.g., precision, throughput, and dependability, lead to these evolution steps. A detailed description of the PPU's evolution scenarios was elaborated for the priority programme [10].…”

“…The techniques are evaluated on the CoCoMe case study, particularly with the scenario of moving a database from one cloud provider to another while complying with data policy requirements. 9 http://www.dfg-spp1593.de/evoline. 10 http://www.dfg-spp1593.de/fypa2c.…”

Interaction of model-driven engineering and signal-based online monitoring of production systems: Towards Requirement-aware evolution

“…Indisputable, both types of modification scenarios occur and are preferred in different kinds of situations [30]. As a consequence, an efficient evolution support for production systems must allow both types of scenarios [31]. Therefore, the following section presents synergies and a possible combination of the previously presented approaches.…”