An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.

Model-based training of manual procedures in automated production systems

Maintenance engineers deal with increasingly complex automated production systems (aPSs). Such systems are characterized by an increasing computerization or the addition of robots that collaborate with human workers. The effects of changing or replacing components of such systems are difficult to assess since there are complex interdependencies between process parameters and the state of the components. This paper proposes a model-based training system that visualizes these interdependencies using domain-independent SysML models. The training system consists of a virtual training system for initial training and an online support system for assistance during maintenance or changeover procedures. Both systems use structural SysML models to visualize the state of the machine at a certain step of a procedure. An evaluation of the system in a changeover procedure against a paper-based manual showed promising results regarding effectiveness, usability and attractiveness.Comment: 25 pages, https://www.sciencedirect.com/science/article/pii/S095741581830080

Increasing System Test Coverage in Production Automation Systems

An approach is introduced, which supports a testing technician in the identification of possibly untested behavior of control software of fully integrated automated production systems (aPS). Based on an approach for guided semi-automatic system testing, execution traces are recorded during testing, allowing a subsequent coverage assessment. As the behavior of an aPS is highly dependent on the software, omitted system behavior can be identified and assessed for criticality. Through close cooperation with industry, this approach represents the first coverage assessment approach for system testing in production automation to be applied on real industrial objects and evaluated by industrial experts

Systematic Model-based Design Assurance and Property-based Fault Injection for Safety Critical Digital Systems

With advances in sensing, wireless communications, computing, control, and automation technologies, we are witnessing the rapid uptake of Cyber-Physical Systems across many applications including connected vehicles, healthcare, energy, manufacturing, smart homes etc. Many of these applications are safety-critical in nature and they depend on the correct and safe execution of software and hardware that are intrinsically subject to faults. These faults can be design faults (Software Faults, Specification faults, etc.) or physically occurring faults (hardware failures, Single-event-upsets, etc.). Both types of faults must be addressed during the design and development of these critical systems. Several safety-critical industries have widely adopted Model-Based Engineering paradigms to manage the design assurance processes of these complex CPSs. This thesis studies the application of IEC 61508 compliant model-based design assurance methodology on a representative safety-critical digital architecture targeted for the Nuclear power generation facilities. The study presents detailed experiences and results to demonstrate the benefits of Model testing in finding design flaws and its relevance to subsequent verification steps in the workflow. Additionally, to study the impact of physical faults on the digital architecture we develop a novel property-based fault injection method that overcomes few deficiencies of traditional fault injection methods. The model-based fault injection approach presented here guarantees high efficiency and near-exhaustive input/state/fault space coverage, by utilizing formal model checking principles to identify fault activation conditions and prove the fault tolerance features. The fault injection framework facilitates automated integration of fault saboteurs throughout the model to enable exhaustive fault location coverage in the model

A methodology for the design of quality assurance functional model and information system

In spite of all advances in computer, technologies, information processing, automation technologies, manufacturing processes, and the push for integration across all functional areas toward a totally integrated and automated manufacturing system, the suggestion is that quality assurance which covers all quality-based functions in the product-life cycle is often overlooked. In spite of the important role of quality information systems in achieving high quality processes little published research in this area is found in the literature. Study of the available relevant literature and the collection of data from manufacturing industries confirm that different manufacturing situations require different quality assurance systems, and this is evident from the proliferation of differing QA systems found in industry. There are however some common features both universal/or within different classes of industries. Accordingly an 'ISO-9000 based generic structural model incorporating these common quality based functions and their associated information requirements has been developed. This research further investigates and verifies those factors which may affect the design of a QAIS as a guide for designing Quality Assurance Information Systems for manufacturing business organisations. Realising that knowledge-based systems can provide a support environment for designing QAIS, this research also considers and, develops a KB Decision System for Designing Quality Information Systems (DSDQAIS). The DSDQAIS recommends the structure of a QAIS, in the form of an IDEFO model, appropriate to specific company profiles input by the user. Since the available software' applications and development tools which support the sub-systems run on a personal computer, the prototype of this system has also been developed and tested on PC. Recommendations for the further development of the system are given

Enhanced Planning Of Production Plants: A Case-Based Reasoning Driven Approach

Advanced industrial developments lead to increasingly customized products and shortened product life cycles. In the context of production systems, this necessitates faster engineering of suitable production resources and layouts to cope with the increasing product variety. Current engineering processes rely mainly on adapting already realized solutions and leveraging past experiences to address new project challenges. However, the knowledge about efficient planning processes is often tied to individual employees. These experiences cannot be utilized consistently, particularly in employee departure or absence due to illness. To counteract this problem, companies attempt to digitize and store knowledge in various ways. Nevertheless, the company-wide and person-independent retrieval of crucial information is still difficult or impossible. Influencing factors are, among others, non-standardized information models and forms of description. In response to these challenges, this paper introduces an approach for the standardized modeling and crosscompany provision of experiences in production plant planning. Based on the paradigms of case-based reasoning and vendor-neutral data modeling using AutomationML, a system for selecting production resources and planning related layouts is demonstrated. By determining the similarity of new product structures, whose production facilities have yet to be engineered, with products whose production facilities are already realized, suitable existing solutions regarding production resources and their placement can be submitted explicitly to a planning expert. The approach is exemplified by a scenario of engineering an assembly system for electrolysis stacks. For this purpose, the similarity determination is performed using the Hamming similarity. Thus, it can be shown that case-based reasoning, which is already successfully used in other domains, has a significant potential to accelerate the subprocesses of production plant planning

Jätevedenpuhdistamojen prosessinohjauksen ja operoinnin kehittäminen data-analytiikan avulla: esimerkkejä teollisuudesta ja kansainvälisiltä puhdistamoilta

Instrumentation, control and automation are central for operation of municipal wastewater treatment plants. Treatment performance can be further improved and secured by processing and analyzing the collected process and equipment data. New challenges from resource efficiency, climate change and aging infrastructure increase the demand for understanding and controlling plant-wide interactions. This study aims to review what needs, barriers, incentives and opportunities Finnish wastewater treatment plants have for developing current process control and operation systems with data analytics. The study is conducted through interviews, thematic analysis and case studies of real-life applications in process industries and international utilities. Results indicate that for many utilities, additional measures for quality assurance of instruments, equipment and controllers are necessary before advanced control strategies can be applied. Readily available data could be used to improve the operational reliability of the process. 14 case studies of advanced data processing, analysis and visualization methods used in Finnish and international wastewater treatment plants as well as Finnish process industries are reviewed. Examples include process optimization and quality assurance solutions that have proven benefits in operational use. Applicability of these solutions for identified development needs is initially evaluated. Some of the examples are estimated to have direct potential for application in Finnish WWTPs. For other case studies, further piloting or research efforts to assess the feasibility and cost-benefits for WWTPs are suggested. As plant operation becomes more centralized and outsourced in the future, need for applying data analytics is expected to increase.Prosessinohjaus- ja automaatiojärjestelmillä on keskeinen rooli modernien jätevedenpuhdistamojen operoinnissa. Prosessi- ja laitetietoa paremmin hyödyntämällä prosessia voidaan ohjata entistä tehokkaammin ja luotettavammin. Kiertotalous, ilmastonmuutos ja infrastruktuurin ikääntyminen korostavat entisestään tarvetta ymmärtää ja ohjata myös eri osaprosessien välisiä vuorovaikutuksia. Tässä työssä tarkastellaan tarpeita, esteitä, kannustimia ja mahdollisuuksia kehittää jätevedenpuhdistamojen ohjausta ja operointia data-analytiikan avulla. Eri sidosryhmien näkemyksiä kartoitetaan haastatteluilla, joiden tuloksia käsitellään temaattisen analyysin kautta. Löydösten perusteella potentiaalisia ratkaisuja kartoitetaan suomalaisten ja kansainvälisten puhdistamojen sekä prosessiteollisuuden jo käyttämistä sovelluksista. Löydökset osoittavat, että monilla puhdistamoilla tarvitaan nykyistä merkittävästi kattavampia menetelmiä instrumentoinnin, laitteiston ja ohjauksen laadunvarmistukseen, ennen kuin edistyneempien prosessinohjausmenetelmien käyttöönotto on mahdollista. Operoinnin toimintavarmuutta ja luotettavuutta voitaisiin kehittää monin tavoin hyödyntämällä jo kerättyä prosessi- ja laitetietoa. Työssä esitellään yhteensä 14 esimerkkiä puhdistamoilla ja prosessiteollisuudessa käytössä olevista prosessinohjaus- ja laadunvarmistusmenetelmistä. Osalla ratkaisuista arvioidaan sellaisenaan olevan laajaa sovelluspotentiaalia suomalaisilla jätevedenpuhdistamoilla. Useiden ratkaisujen käyttöönottoa voitaisiin edistää pilotoinnilla tai jatkotutkimuksella potentiaalisten hyötyjen ja kustannusten arvioimiseksi. Jo kerättyä prosessi- ja laitetietoa hyödyntävien ratkaisujen kysynnän odotetaan tulevaisuudessa lisääntyvän, kun puhdistamojen operointi keskittyy ja paineet kustannus- ja energiatehokkuudelle kasvavat

Quality 4.0 in action: Smart hybrid fault diagnosis system in plaster production

UIDB/00066/2020Industry 4.0 (I4.0) represents the Fourth Industrial Revolution in manufacturing, expressing the digital transformation of industrial companies employing emerging technologies. Factories of the future will enjoy hybrid solutions, while quality is the heart of all manufacturing systems regardless of the type of production and products. Quality 4.0 is a branch of I4.0 with the aim of boosting quality by employing smart solutions and intelligent algorithms. There are many conceptual frameworks and models, while the main challenge is to have the experience of Quality 4.0 in action at the workshop level. In this paper, a hybrid model based on a neural network (NN) and expert system (ES) is proposed for dealing with control chart patterns (CCPs). The idea is to have, instead of a passive descriptive model, a smart predictive model to recommend corrective actions. A construction plaster-producing company was used to present and evaluate the advantages of this novel approach, while the result shows the competency and eligibility of Quality 4.0 in action.publishersversionpublishe

Production planning process optimization

Produktionsautomationssysteme sind komplexe Systeme mit viele Entitäten (Roboter, Transportsysteme usw.) die mannigfaltig aufeinander einwirken und zusammenspielen um das Ziel einer Produktendfertigung zu ermöglichen. Multiagenten-Systeme basierend auf verteilter Kontrolle sind der praktikabelste Ansatz die ansteigende Kompliziertheit solcher Systeme in den Griff zu bekommen und gleichzeitig eine flexible Anpassung des Produktionsautomationssystems an variable Rahmenbedingungen zu gewährleisten (z.B. Änderung von Produktionsstrassen oder die Koordination von Transportelementen). Für solch kritische Produktionsautomationssysteme ist eine Überprüfung aller Schritte im Entwicklungsprozess erforderlich um ein sicher funktionierendes System zu gewährleisten. Qualitätsmessungen zur Sicherstellung der Korrektheit von Systemelemente stellen bei der Zielerreichung daher einen wichtigen Schritt dar. Die Softwaresimulation des Werkstatt-Systems erlaubt sowohl Leistungsmessung einer Systemkonfiguration als auch schnellere und preiswertere Reaktion auf sich ändernde Voraussetzungen. Hinzu kommt, dass die Softwaresimulation von Produktionsautomationssystemen immer mehr einen praktikable Möglichkeit darstellt, um Produktionsvorgänge zu planen und/oder zu optimieren.Production Automation Systems are complex systems. They typically have many entities like robots, transport systems, etc. that interact in complex ways to provide production automation functions like assembly of products. The increasing complexity of these systems makes central control more and more difficult. Therefore systems with distributed control are areas of intense research such as multi-agent systems. Moreover, changing requirements for production automation systems require better system and model flexibility for e.g. easy-to-change workshop layouts or coordination of transportation elements. Meeting all this tasks makes the design of a production automation system a challenge hard to solve for designers and system engineers. For safety-critical systems like production automation systems, verification is required for all steps in the development process. Testing aims at measuring the quality of executable system elements, especially the validity of a configuration and correctness of calculated results. A particular challenge is measurement of non-functional quality requirements such as system performance before the actual hardware system is built. Software simulation of the workshop system would allow both performance measurement of a configuration and faster, cheaper reaction to changing requirements, however the validity of the simulation has to be assured. On top of this, software simulation of production automation systems can get more and more a sufficient part during the production planning and optimization process