Search

Um das Design von Automatisierungssystemen noch beeinflussen zu können, müssen Security-Entscheidungen früh während des Automation-Engineering-Workflows getroffen werden („Security by Design“). Doch die beteiligten Ingenieurinnen und Ingenieure wissen oft gar nicht, welche Security-Entscheidungen sie wann treffen müssten – oder mit ihren Design-Festlegungen implizit sowieso treffen. Das vorgestellte „Automation Security by Design Decisions“-Konzept baut auf Security- Entscheidungen als zentralem Element auf und bevorzugt Security-Maßnahmen, die durch die Nutzung systemimmanenter Eigenschaften anstatt zusätzlicher Security-Lösungen umsetzbar sind. Diese systematische Entscheidungsfindung befähigt Ingenieurinnen und Ingenieure der am Automation-Engineering-Workflow beteiligten Gewerke, „ihre“ Security-Entscheidungen auch ohne dediziertes Security-Knowhow selbst zu treffen.

„Security by Design“, also das Treffen von Security-Entscheidungen schon während des Engineerings von Automatisierungssystemen, ist ein häufig formuliertes Idealbild für Security in der Industrie. Doch zu häufig bleibt es bei diesem gut klingenden, aber vagen Begriff. Was Security by Design für Automatisierungssysteme eigentlich genau bedeutet (oder bedeuten müsste) und wie es praktisch umzusetzen wäre, ist ungeklärt. Dieser Beitrag klärt Grundbegriffe zu Security by Design und analysiert existierende Ansätze anhand der Mechanismen, wie Security in den Engineering-Workflow integriert wird. Schlussendlich werden Anforderungen an ein Konzept abgeleitet, das Security by Design für Automatisierungssysteme in der Praxis anwendbar macht.

Im ersten Teil dieses Beitrages wurde die Notwendigkeit von intermodularen Sicher­heits­konzepten zur Beherrschung intermodularer Risiken hergeleitet und begründet. In diesem zweiten Beitragsteil wird das hierzu entwickelte Konzept einer funktionalen Sicherheitsschicht für den modularen Anlagenbau vorgestellt. Analog zur betrieblichen Orches­trierung auf dem Process Orchestration Layer, wird für die Sicherheitsorchestrierung der Begriff des functional Safety Orchestration Layer vorgeschlagen. Zur Reduktion des damit einhergehenden Engi­neering-Aufwandes werden eine Kommunikationsarchitektur konzipiert, Varianten zur Vereinfachung des Safety-Engineerings beleuchtet sowie die Implementierung einer serviceorientierten Kommunikation über sogenannte Safety-Services integriert. Diese Aspekte sollen in einem Safety-MTP zusammengeführt werden. Abschließend wird die hardwaretechnische Um­setzung eines intermodularen Safety Integrated System beschrieben und anhand eines einfachen Demonstrators validiert.

Industrial signal measurement and processing are increasingly being deployed in control performance assessment, particularly in oscillation monitoring applications. In this paper, we present a nove...

Industrial oscillation recordings are often contaminated with random noise, process disturbances and underlying nonstationarity, which obscure the useful information of the signal and complicate subsequent oscillation detection and diagnosis. This paper proposes a novel denoising technique to improve the quality of oscillation data, by jointly employing ensemble empirical mode decomposition (EEMD) with canonical correlation analysis (CCA). The proposed method first utilizes EEMD to decompose the single-loop data into a set of intrinsic mode functions (IMFs). Then CCA is applied to isolate the oscillation-dependent components from the decomposed IMFs. We evaluated the performance of the method through both numerical and industrial examples. The results demonstrate that this work is a promising tool for oscillation data preprocessing in the single control-loops.

Seit einigen Jahren wird seitens der Industrie intensiv an einer neuen Automatisierungsarchitektur für die Prozessindustrie gearbeitet. Da die Initiative hierzu aus den USA kam, sind die Arbeiten und ersten Ergebnisse in Deutschland zwar grundsätzlich bekannt, werden jedoch aus Sicht des Autors noch zu wenig inhaltlich diskutiert. Als Konsequenz liegen bislang kaum deutsche Veröffentlichungen hierzu vor [1]. Der vorliegende Artikel möchte diese Lücke schließen, indem er einen Bogen schlägt von der Motivation der Arbeiten über die aktuell erreichten Ergebnisse bis hin zu einer Einschätzung, die als Debattenbeitrag angesehen werden soll. Ziel ist es, die Diskussion über eine neue Automatisierungsarchitektur und damit einhergehende veränderte Geschäftsmodelle im deutschsprachigen Raum zu intensivieren.

Zur Effizienzsteigerung in der Automatisierung wird die Digitalisierung vorangetrieben. Für die Vernetzung (z.B. Erfassung von Diagnosedaten, Fernwartung...) werden auch öffentliche bzw. teilöffentliche Netze wie WLAN, Mobilfunk oder Internet herangezogen. Da Angriffe aus dem Internet bereits heute auf die Automatisierung übergreifen muss auch hier die Verwendung gesicherter Kommunikation vorangetrieben werden. Funktional sichere Protokolle müssen somit auch über verschlüsselte Kommunikation möglich sein. Daher ist es erforderlich, etablierte Standards und Technologien neu zu bewerten.

Der Austausch zwischen Industrie und Wissenschaft im Ingenieurwesen ist von besonderer Bedeutung. Eine effektive, aber oftmals wenig gelebte Form des Austauschs ist die Aufnahme von Gastvorträgen durch Industrieexperten in den Lehrplan. In diesem Beitrag werden Beispiele für Lehrbeauftrage der Industrie innerhalb der Regelungs- und Automatisierungstechnik vorgestellt sowie ein Überblick über entsprechende Vorträge von ABB-Mitarbeitern gegeben. Ein konkretes Beispiel zeigt, wie ein Regelkreis im Zusammenhang mit der Automatisierung verstanden wird. Die Voraussetzungen für einen erfolgreichen Austausch sowie die Vorteile für Studierende, Wissenschaftler und Industrievertreter werden diskutiert.

Oscillations that propagate throughout a plant can have severe impacts on an industrial process. It is important and challenging to automatically detect and diagnose such oscillations in order to maintain efficient operation. A novel algorithm, multivariate intrinsic time-scale decomposition (MITD), is proposed to characterize the oscillatory behavior. It extends univariate intrinsic time-scale decomposition (ITD) by solving an overdetermined system of linear equations. To optimize the decomposition performance, several approaches are proposed which include (i) uniformly projection method, (ii) redefinition of proper rotation component for ITD and (iii) end effect restraining. The advantage of the developed method is that the investigated multi-dimensional signal can be analyzed under both time and frequency scales. Unlike other methods, both the regularity of the plant-wide oscillations (in frequency domain) and evolution of the local characteristics (in time scale) can be well captured via MITD. It is a...

The multivariate empirical mode decomposition (MEMD) has been pioneered recently for adaptively processing of multichannel data. Despite its high efficiency on time-frequency analysis of nonlinear and nonstationary signals, high computational load and over-decomposition have restricted wider applications of MEMD. To address these challenges, a fast MEMD (FMEMD) algorithm is proposed and featured by the following contributions: 1) A novel concept, pseudo direction-independent multivariate intrinsic mode function (IMIMF) which allows the interchange of sifting and projection operations, is defined for the purpose of developing FMEMD; 2) FMEMD is computationally efficient. Compared with MEMD, the number of time-consuming sifting operations reduces from $K \cdot p$ to $K$ for each iteration, where $K$ and $p$ denote the number of projection directions and signal dimension, respectively; 3) FMEMD is consistent with EMD in terms of the dyadic filter bank property; and 4) FMEMD is more effective in working at low sampling rate. Validity of the raised approach is demonstrated on a wide variety of real world applications.

This paper proposes a novel time-frequency method for plant-wide oscillation analysis based on the multivariate extension of standard empirical mode decomposition (EMD). The raised fast multivariate empirical mode decomposition (FMEMD) is generalized from EMD by solving an overdetermined system of linear equations. Due to its capability to analyze multiple channels data, FMEMD is especially suitable for characterizing plant-wide control loop oscillations. Unlike traditional methods, both the regularity of oscillations (in frequency domain) and evolution of local characteristics (in time scale) can be well captured via FMEMD. Validity of the raised approach is demonstrated on simulations as well as an industrial case.

The exchange between industry and academia is important in engineering in general and in control engineering in particular. One effective but not often considered form of exchange is inclusion of guest lectures by industry experts in the syllabus. This paper discusses examples of industrial lecturers in process control and automation and gives an overview of lectures delivered by ABB employees. A concrete example details how a feedback control loop is seen in the context of automation. Prerequisites for a successful exchange are discussed and benefits for students, academics and industry were collected.

A novel online detector for multiple oscillations in process industry is proposed. This article is motivated by the fact that it is still an open problem to design a real-time monitor which is suitable for detecting multiple oscillations with signal intermittency and non-linear/non-stationary properties. The proposed approach of Intrinsic Time-scale Decomposition (ITD) with Robust Zero crossing intervals Clustering (ITD-RZC) (i) provides an experimental statistic to remove noisy zero-crossings intervals (ZCIs), (ii) develops a novel adaptive robust K-means ZCI clustering which enables the reconstructed Proper Rotation Component (PRC) to encapsulate the sporadic oscillation and (iii) proposes an effective online-cluster-updating mechanism for real-time intermittent oscillations detection. ITD-RZC approach is computationally efficient and capable of preserving nonlinear features of the process variables which facilitates subsequent oscillation diagnosis. Simulation examples and industrial cases study are provided to demonstrate the effectiveness of the proposed online oscillation detector.

A novel method based on improved local mean decomposition (LMD) for oscillation detection is proposed. Due to its capability to analyze amplitude and frequency modulated signals, LMD is especially suitable for characterizing time-varying control loop oscillations. In contrast to empirical mode decomposition (EMD), the improved LMD performs better in the following aspects: (i) ability to extract both single/multiple oscillations in process output, (ii) robustness to noise, and (iii) capability to handle non-stationary trends. In addition, improved LMD can precisely characterize the time-varying oscillations without distortion and frequency leakage even for short time series. Finally, a robust Lempel–Ziv complexity based statistic for time-varying oscillation detection is presented. Simulation examples and industrial applications are provided to demonstrate the effectiveness of the proposed LMD oscillation detector.

This paper presents the control loop data of industrial controllers that are recently made available online. All data is confirmed and some of it has been published previously to develop fault detection and diagnosis methods. Methods to detect faults that occur during the operation of an industrial process are important and have attracted attention previously but are not always widely used in industry. One of the reasons is that any method needs to be robust and fully automated. The purpose of the data repository is to present data to test methods so that false positives and negatives are reduced to an insignificant number. Three previously published methods – oscillation detection based on the autocorrelation function, the idle index and a method for quantization detection – together with a simple, novel saturation detection method and one new detection methods are applied to all industrial data. The results are discussed and ways to improve the robustness and automation potential of these methods.

Control loop performance monitoring (CPM) in industrial production processes is an established area of research for which many methods to detect malfunctioning loops have been developed. However, it is unclear which methods are successful in an industrial environment. Often, there are additional aspects such as organizational issues, data availability and access that can compromise the use of CPM. In this paper, we are reporting on the results of a survey amongst CPM users. The survey takes stock of existing methods and their use in industry as well as which faults are most frequent and can be detected. Organizational as well as implementation issues are investigated and discussed. This paper aims to identify open research topics and the direction of development of CPM in industrial production processes.

Video lectures are finding their way into education - there are numerous advantages and they can be used in different contexts within formal, non-formal and informal education. Control systems is a subject in formal education that can be viewed from a practitioner's angle. This paper describes a video lecture on control systems that is sponsored by ABB and available on YouTube. The lecture was developed by control practitioners for an audience that (1) does not have a strong engineering background and (2) have an engineering background but has not been shown the linkage to the real world. The difference between formal control systems lectures and this course are discussed.

An online detector for time-variant oscillations in univariate time-series is proposed. This paper is motivated by the fact that it is still an open problem to design a real-time oscillation detector which is applicable to non-linear, non-stationary and intermittent oscillations. The proposed procedure is based on intrinsic time-scale decomposition (ITD) and contains (i) an improved iteration termination condition for ITD with on-line back-redecomposition and (ii) a novel hypothesis test with a robust statistic of variation coefficient which enables online monitoring of time-variant oscillations. The proposed approach is computationally efficient, does not require a priori supervision window and is better applicable for online detection of time-variant oscillations. In addition, it preserves nonlinear features in process variables which facilitates subsequent oscillation diagnosis. Simulation examples and industrial applications are provided to demonstrate the effectiveness of the proposed online oscillation detector.

An automatic detection technique of nonstationary multiple oscillations in industrial control loops is proposed. The technique is based on an improved wavelet packet transform (WPT) which integrate...

An online detector for time-variant oscillation in a univariate time-series is proposed. This paper is motivated by the fact that it is still an open issue to implement the realtime oscillation detector which is applicable to non-linear, non-stationary and intermittent oscillations. The proposed procedure is based on Intrinsic Time-scale Decomposition (ITD) and contains an improved iteration termination condition of ITD. A novel hypothesis test with an improved statistic of variation coefficient enables the online monitoring of the time-variant oscillations. Simulation examples and industrial applications are provided to demonstrate the effectiveness of the online detector.

The Choudhury valve model is a widely adopted data-driven model to study the behaviour of valve stiction. A recent study ( Garcia, 2008 ) revealed that valve stiction simulation based on Choudhury’s simulation model ( Choudhury, Thornhill, & Shah, 2005 ) fails to pass eight out of fifteen Industry Standard Architecture (ISA) standard tests ( ISA, 2000 , ISA, 2006 ) for real control valves. In this study, the ISA testing results are further elaborated for this model. It is found that three minor deficiencies lead to the discrepancies between the Choudhury Model outputs and the expected ones when (i) the valve input signal changes the direction of travel, (ii) the initial stem position does not stay on the working curves l1 and l2, and (iii) the valve input signal changes in a ramp–pause–ramp manner. To address the above deficiencies, an improved version of the Choudhury Model, termed as XCH Model, is proposed. Assessments along with the ISA standards presented by Garcia (2008 ) demonstrate the proposed XCH Model passes all the ISA standard tests and thus provides a more realistic simulation of a real industrial valve being able to exhibit stiction behaviour.

In Germany, the term ?Industrie 4.0 [1] is currently prevalent in almost every industry-related fair, conference, or call for public-funded projects. First used at the Hanover Fair in 2011, the term, raised numerous discussions, and the major question is: is it a hit or hype? Even in politics, this term is used frequently with respect to German industry, and research efforts relating to it are currently supported by ?200 million from government-funding bodies?the German Federal Ministry of Education and Research and the German Federal Ministry of Economic Affairs and Energy. The term Industrie 4.0 refers to the fourth industrial revolution and is often understood as the application of the generic concept of cyberphysical systems (CPSs) [5]?[7] to industrial production systems (cyberphysical production systems). In North America, similar ideas have been brought up under the name Industrial Internet [3], [4] by General Electric. The technical basis is very similar to Industrie 4.0, but the application is broader than industrial production and also includes, e.g., smart electrical grids. The various definitions have caused confusion rather than increasing transparency. Overambitious marketing reinforced the confusion (Industrie 4.0 is already being done). This obscures the real and sound future visions behind Industrie 4.0. This column is intended to provide easy-to-understand access to the core ideas of Industrie 4.0 and describes the basic industrial requirements that need to be fulfilled for its success.

This article reviews advances in detection and diagnosis of plant-wide control system disturbances in chemical processes and discusses new directions that look promising for the future. Causes of plant-wide disturbances include non-linear limit cycles in control loops, controller interactions and tuning problems. The diagnosis of non-linearity, especially when due to valve stiction, has been an active area. Detection of controller interactions and disturbances due to plant structure remain open issues, however, and will need new approaches. For the future, the linkage of data-driven analysis with a qualitative model of the process is an exciting prospect. Finally, the paper offers some brief comments about emerging applications.

This article reviews advances in detection and diagnosis of plant-wide control system disturbances in chemical processes and discusses new directions that look promising for the future. Causes of plant-wide disturbances include non-linear limit cycles in control loops, controller interactions and tuning problems. The diagnosis of non-linearity, especially when due to valve stiction, has been an active area. Detection of controller interactions and disturbances due to plant structure remain open issues, however, and will need new approaches. For the future, the linkage of data-driven analysis with a qualitative model of the process is an exciting prospect that now looks within reach. Finally, the paper offers some comments about emerging applications.

The evaluation of control performance by means of performance indices from large amounts of measurement data is investigated. The focus is twofold: Firstly to assess information that can be deduced from many data sets and secondly to investigate the usefulness of simple performance measures. Established methods and some useful new ideas are evaluated on many industrial data sets and the results are discussed

An appealing index for detection of sluggish control loops has been proposed by Hagglund (Control Eng. Practice 7 (1999) 1505). When dealing with real, noisy data, however, the index value depends heavily on the data pre-treatment. This paper describes ways to compute the Idle Index under realistic conditions. Examples are shown and additional problems that might occur are discussed. Furthermore, the case of non-stepwise disturbances is discussed.

Several approaches to automatic control performance assessment have been proposed in recent years, among which the one by Harris has received much attention in particular. One thing that is not automatically assessed by computing a performance index, is whether the controller uses an appropriate sampling frequency. In this paper, an approach is proposed which allows the evaluation of Harris’ performance index at sampling rates faster than that used for data collection. The new method is illustrated using data from the Swedish pulp and paper industry. When the dead-time is not the main performance limiting factor, the Harris index is known to produce overly pessimistic values. Therefore, a modified index was also presented and evaluated for the examples. The conclusion is that by using the modified index it is possible to get an indication of the benefit of faster sampling.

A control performance index which relates actual output variance to minimal achievable variance was first presented by Harris [T.J. Harris, Assessment of control loop performance, The Canadian Journal of Chemical Engineering 67 (1989) 856–861]. In the present paper, a modification of that index is applied. Instead of comparing to minimum variance control — which corresponds to placing all closed-loop poles in the origin — one pole is placed using either control design guidelines or additionally available process knowledge. Some possible choices of the free closed-loop pole are discussed. Based on this modified closed-loop system, a performance index can be calculated which relates actual output variance to the minimum achievable variance using the modified closed-loop system. It is shown that for the calculation of this index no other information apart from the measured process output and the time-delay is necessary. Furthermore, a method is presented which allows the assessment of the accuracy of the calculated index. The original Harris index and the proposed modified index are computed using data from industrial processes.

A simple method diagnosing oscillations in process control loops is presented. The new method is based on the cross-correlation between control input and process output and it is shown to correctly distinguish between two important reasons for oscillations in control loops in the process industry, namely external oscillating disturbances and static friction (stiction) in control valves.

There has been an increasing interest in automatic control performance monitoring in recent years. The aim of such monitoring tools is to detect deterioration such as increased variability, oscillating behaviour, saturation or off-sets. Easy and efficient methods have been presented in the literature. After having detected a deteriorated control performance, one would like a monitoring tool to give hints of the possible cause of the deterioration. We will in this contribution suggest a method which allows automatic classification of one important reason for a detected control performance deterioration, namely static friction (stiction) in control valves. The suggested approach uses methodology from the fault-detection field and involves a model-based nonlinear observer and statistical hypothesis testing using a likelihood ratio test. Only little process knowledge, as time-delay, measurements of control signal and process output and some usually known valve parameters are needed. The method is evaluated on industrial data.

The aim of this paper is to describe a model for dynamic simulation of a TMP refiner. The temperature profile along the radius of the refiner, outlet consistency and motor load are considered as outputs of the simulation, whereas the chip screw speed and dilution water flow setpoints are the inputs. The dynamic model of the refiner, as such, has been derived from first principles. The motor load and input dynamics, however, are based on black-box identifications. The model has been implemented in MATLABISIMULINK. Simulations are compared to corresponding data from experiments with the refiner.

Summary form only given. There is a considerable gap between academic research and industrial practice in the area of fault detection, fault isolation and fault-tolerant control. Reasons for this are manifold and will be discussed based on concrete examples from industry. On one side there are increasing requirements on operational excellence in process plants. On the other side there is only a minimal workforce available for operation and maintenance. Automation of fault detection and isolation on one side and fault-tolerance on the other side should therefore be self-evident. They are, however, not. The talk will discuss reasons for this and show examples from industry where those obstacles have been overcome. As a consequence, some possible directions for academic research as well as success criteria will be pointed out.

Among the methods that aim to detect stiction, quite a few focus on analysing the specific signal shapes that loops exhibiting stiction usually show. The idea to use cross-correlation to investigate the signal shape for control loop data has triggered quite some further research in this area. Cross-correlation-based detection is introduced and shown to robustly indicate a stiction behaviour in many typical industrial cases. The chapter then presents a theoretical explanation why cross-correlation can robustly detect more or less typical stiction patterns and also states where it should not be used. There are, however, cases where cross-correlation will give misleading results, the most important being processes that are of an integrating nature (level control). For such loops, an alternative to cross-correlation needs to be offered. Such an approach that is signal-shape based is presented afterwards. Interestingly, the same approach can also be used for self-regulating (i.e. non-integrating) loops as well.