Evolution of software in automated production systems

This abstract summarizes the paper accepted at the Journal of Systems and Software with the same title [1]. 
Automated production systems form the backbone of the world’s industrial production. They are highly specialized technical systems, which are comprised of mechanical, electrical and electronic parts and software, all closely interwoven. Software is the defining factor to realize modern trends in manufacturing as defined by mass customization, small lot sizes, high variability of product types, and a changing product portfolio during the lifecycle of an automated production system. However, the software can control the production system only via electrical and mechanical means, which have their individual life cycles and undergo evolution. Hence, the evolution of automated production systems always requires addressing cross-disciplinary evolution challenges.
We provide an interdisciplinary survey on the challenges, the state-of-the-art as well as research directions with respect to the evolution of software in automated production systems. In the first part, we discuss the specifics of the development process as well as the different types of evolutions during the system’s life-cycle. In the second part, we survey the challenges due to evolution covering the different development phases (requirements, design, implementation, validation & verification) and several important cross-cutting aspects (variability management, model-driven engineering, and traceability), and review existing potential approaches. Finally, we outline future research directions for the discussed challenges.

Evolution of software in automated production systems: Challenges and Research Directions

After the introduction of fieldbus technology, real-time Ethernet (RTE) systems now form the second generation of industrial communication systems (2G ICS). A lot of different approaches for RTEs appeared during the last years, most of them optimized for specific use cases or application domains. From a user's perspective, the transition from a proved fieldbus system to a RTE only makes sense, if multiple system properties are improved significantly in comparison to the state-of-the-art. In order to address such main requirements of machine builders, we introduced three building blocks as key components for a generic RTE system, these includes topology-based addressing, optimized datagram transfer, and synchronous scheduling.

A Proposal for a Generic Real-Time Ethernet System

Electricity, water or air are some Industrial energy carriers which are struggling under the prices of primary energy carriers. The European Union for example used more 20.000.000 GWh electricity in 2011 based on the IEA Report [1]. Cyber Physical Production Systems (CPPS) are able to reduce this amount, but they also help to increase the efficiency of machines above expectations which results in a more cost efficient production. Especially in the field of improving industrial plants, one of the challenges is the implementation of anomaly detection systems. For example as wear-level detection, which improves maintenance cycles and thus leads to a better energy usage. This paper presents an approach that uses timed hybrid automata of the machines normal behavior for a predictive maintenance of industrial plants. This hybrid model reduces discrete and continuous signals (e.g. energy data) to individual states, which refer to either the present condition of the machines. This allows an effective anomaly detection by implementing a combined data acquisition and anomaly detection approach, and the outlook for other applications, such as a predictive maintenance planning. Finally, this methodology is verified by three different industrial applications.

System modeling based on machine learning for anomaly detection and predictive maintenance in industrial plants

The increasing complexity of today's production systems and the variety of model-based approaches to their monitoring, diagnosis and testing emphasize the importance of the modeling step. Modeling is mostly done manually, in a costly and time-consuming way. In this paper, an alternative that comes from the learning theory is given: an automated procedure for identifying behavior models from recorded observations. Assuming the system's structure is known, the algorithm presented here is capable of learning behavior models for its components. The algorithm accounts for probabilistic, timing, discrete and continuous aspects of the given system, using the modeling formalism of hybrid automata. The practical usability of identified models is demonstrated using an anomaly detection application for a real production system.

Identifying behavior models for process plants

Validation of non-functional and functional properties of these protocols during the early stages of design and development is important to reduce cost resulting from protocol anomalies, design errors like deadlock or livelock situations and/or violations of time constraints. The MDD approach promises a well-adapted formalism to bridge real-time protocol complexities and time to market pressure. UML with its several diagrams, supports techniques to overcome the aforementioned complexities. It also supports quantitative analysis through its real-time profiles. This paper reviews the most important real-time UML profiles which can be used for designing time-critical Industrial Communication Protocols (ICPs).

/pdf/uml-profiles-for-modeling-real-time-communication-protocols-5e3onuv36w.pdf

UML Profiles for Modeling Real-Time Communication Protocols

Model-driven system/protocol engineering has been successfully applied in the industrial automation domain over the recent years. However, its cousin model-based testing (MBT) is relatively a new kid in the block — who is being curiously observed by domain experts. MBT leverages behavior models (e.g. software models) to automatically generate a large set of test cases. Testing industrial communication and automation systems manually for all significant behavioral scenarios is a non-trivial task. Hence, automatic generation of test vectors from formal/semi-formal models is desirable. Here, we report our first step towards the usage of MBT in the industrial automation context.

Model based TTCN-3 testing of industrial automation systems — First results

Model-based approaches have been applied successfully to a wide range of tasks such as specification, simulation, testing, and diagnosis. But one bottleneck often prevents the introduction of these ideas: Manual modeling is a non-trivial, time-consuming task. Automatically deriving models by observing and analyzing running systems is one possible way to amend this bottleneck. To derive a model automatically, some a-priori knowledge about the model structure–i.e. about the system–must exist. Such a model formalism would be used as follows: (i) By observing the network traffic, a model of the long-term system behavior could be generated automatically, (ii) Test vectors can be generated from the model, (iii) While the system is running, the model could be used to diagnose non-normal system behavior. The main contribution of this paper is the introduction of a model formalism called ‘probabilistic regression automaton’ suitable for the tasks mentioned above. Keywords—Model-based approach, Probabilistic regression automata, Statistical models and Timed automata.

Statistical Models of Network Traffic

The engineering of communication protocols is quite difficult and a complex task, as it demands good experience in the field of protocol and system design, implementation, testing, optimization and maintenance of such protocols. In most cases, these protocols are described using informal techniques like informal textual documentations, graphical description techniques, and structural analysis and design. As proven in practice, these lead to ambiguous definitions and lack of definitions because completeness, and consistency cannot be proved. The advent of Unified Modeling Language version 2.0 (UML 2.0) along with its UML Testing Profile (U2TP)in the recent years, promises to be a major break through in the field of formal description techniques. Thus, this work evaluates the suitability of UML 2.0 combined with its Testing Profile for engineering communication protocols using a case study. For experimental case study, this work uses a simple and the most commonly known INRES (Initiator - Responder) protocol. This book is expected to serve as a good starting point for learning UML 2.0 and protocol engineering.

Industrial Communication Protocol Engineering Using UML 2.0

The advent of Unified Modeling Language version 2.0 (UML 2.0) along with its UML testing profile in the recent years, promises to be a major break through in the field of formal description techniques. Thus in this paper we evaluate the suitability of UML 2.0 combined with its Testing profile for the engineering of industrial communication protocols using a case study. For our experimental case study we made use of the simple and most commonly known INRES protocol.

Industrial communication protocol engineering using UML 2.0: A case study

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Barath Kumar

Author Tools

Chat about Author