Paul Wai Hing Chung

HAZID, A Computer Aid for Hazard Identification: 1. The Stophaz Package and the Hazid Code: An Overview, the Issues and the Structure

The hazard and operability, or HAZOP, study is a prime method for the identification of hazards on process plants. This is the first in a series of papers which describes progress in the emulation of hazard identification in the style of HAZOP. The work reported is embodied in a computer aid for hazard identification, or HAZOP emulator, HAZID. The HAZID code is one of a suite of codes developed as part of the STOPHAZ project. The present paper gives an overview of HAZID, with an account of HAZOP and HAZOP emulation, and of the issues underlying it. Companion papers describe the unit model system, the fluid model system and the evaluation of consequences, the evaluation and improvement of HAZID using case studies and other methods, and some development topics. Conclusions from the work are given in the final paper.

An efficient phased mission reliability analysis for autonomous vehicles

Autonomous systems are becoming more commonly used, especially in hazardous situations. Such systems are expected to make their own decisions about future actions when some capabilities degrade due to failures of their subsystems. Such decisions are made without human input, therefore they need to be well-informed in a short time when the situation is analysed and future consequences of the failure are estimated. The future planning of the mission should take account of the likelihood of mission failure. The reliability analysis for autonomous systems can be performed using the methodologies developed for phased mission analysis, where the causes of failure for each phase in the mission can be expressed by fault trees. Unmanned Autonomous Vehicles (UAVs) are of a particular interest in the aeronautical industry, where it is a long term ambition to operate them routinely in civil airspace. Safety is the main requirement for the UAV operation and the calculation of failure probability of each phase and the overall mission is the topic of this paper. When components or sub-systems fail or environmental conditions throughout the mission change, these changes can affect the future mission. The new proposed methodology takes into account the available diagnostics data and is used to predict future capabilities of the UAV in real-time. Since this methodology is based on the efficient BDD method, the quickly provided advice can be used in making decisions. When failures occur appropriate actions are required in order to preserve safety of the autonomous vehicle. The overall decision making strategy for autonomous vehicles is explained in this paper. Some limitations of the methodology are discussed and further improvements are presented based on experimental results.

A SYSTEMATIC HAZOP PROCEDURE FOR BATCH PROCESSES, AND ITS APPLICATION TO PIPELESS PLANTS

Abstract Increasing technological complexity together with social and legal pressures have made it necessary to develop more effective approaches to safety. This need is particularly strong in the design and operation of chemical plants. One approach, Hazard and Operability Study (Hazop), is a method of systematically identifying every conceivable process deviation, its abnormal causes and adverse hazardous consequences in a chemical plant. The technique was developed by ICI in the 1960s, and has been standardised for use in continuous manufacturing plants. Improvised attempts have been made to modify the continuous Hazop approach for use with batch processes, such as using different guide words and deviations, without the method of application being formalised. There are different issues that need to be surmounted for the methodology to be applied to batch processing plants. The standard approach, of examining a system line by line, is ideal for continuous processes but does not lend itself to the thorough examination of batch processes. A typical batch plant can be examined by dividing the process into three operational phases: charge, reaction, and discharge. A modified Hazop methodology should then be applied to the description of each phase. Although a need for this type of approach has been recognised, there is no published information to be found on an agreed format on how this should be done. This paper presents a formalised approach to applying the Hazop methodology to batch processes. A way forward in multi-product manufacturing is the emerging technology of ‘pipeless plants’. The basic idea is to move the process vessel between fixed stations for mixing, separation and other activities. This offers great flexibility for change, and allows a company to respond quickly to market demands and technological advances. Little research has been done on the safety of pipeless plants, which are essentially batch plants with mobile vessels. Therefore the batch Hazop methodology presented in this paper has been further developed in order to improve the safe design of pipeless plants.

Compliance Flow - Managing the compliance of dynamic and complex processes

To develop a reliable system or product, the current best practice for the development process is typically embodied in standards and guidelines, such as IEC61508 for safety and ISO9001 for quality assurance. Generally, the standard proposes a framework, which deals in a systematic manner with all the activities necessary to achieve the required quality. However, every application of a given standard is different because of differences in project details. One serious limitation of current workflow systems is the lack of the ability to ensure that the specification and execution of a process are compliant with the standard. This paper presents the treatment of managing process compliance in the Compliance Flow system. Process-based reasoning is used to identify compliance errors within a user-defined process by matching it against the standard model during both process specification and process execution. Examples drawing on a version of IEC61508 are used to illustrate the mechanism of modelling and compliance checks. A case study of the development of a light-guard is discussed.

A Fuzzy Approach to Accessing Accident Databases

This paper is concerned with accessing information from accident databases. It discusses the limitation of current accident databases and focuses on the issue of finding and ranking of information that relates to a query. A user or system initiates an interaction with a database by specifying what is of interest in the form of a query. The query does not have to be treated as a precise description of what is of interest, but a vague or “fuzzy” one. Fuzzy database techniques make it possible to exploit all available information by returning not only items that match the query exactly, but also items that bear some relation to the query.A domain model for accident reports in the process industries was developed. It consists of four classification hierarchies for the attributesoperation , equipment, cause and consequence. A common approach for assessing how closely two terms are related is based on the number of links between the two terms on a hierarchy. This approach is not appropriate for the accident database domain. Instead, the relationship between any two nodes on a hierarchy is classified into four different types. Methods for determining similarities for the different types of relationships are discussed and have been implemented in an accident database. The ranking of the retrieved information is much more satisfactory then the “distance” based approach.

Use of neural networks in automatic caricature generation: an approach based on drawing style capture

Caricature is emphasizing the distinctive features of a particular face. Exaggerating the Difference from the Mean (EDFM) is widely accepted among caricaturists to be the driving factor behind caricature generation. However the caricatures created by different artists have different drawing style. No attempt has been taken in the past to identify these distinct drawing styles. Yet the proper identification of the drawing style of an artist will allow the accurate modelling of a personalised exaggeration process, leading to fully automatic caricature generation with increased accuracy. In this paper we provide experimental results and detailed analysis to prove that a Cascade Correlation Neural Network (CCNN) can be used for capturing the drawing style of an artist and thereby used in realistic automatic caricature generation. This work is the first attempt to use neural networks in this application area and have the potential to revolutionize existing automatic caricature generation technologies.

Integrating Routing and Scheduling for Pipeless Plants in Different Layouts

Pipeless batch plants are built to provide the ability to adapt to fast market changes. The scheduling of pipeless plants adds new challenges to the scheduling of conventional batch plants. This is because of the requirement to consider the allocation of resources and also the plant layout so that vessels can move from one processing station to another without conflict. This research investigates the integrated problem of scheduling and routing in pipeless plants and develops a constraint-based methodology suitable for different layouts. During the scheduling process, besides time and resource allocation, a planner is also called to find possible routes to move vessels from one processing station to the next proposed station. Each of the dynamically generated routes is immediately check for feasible track allocation so that any infeasible route is discarded as soon as possible to save computational time. A typical scheduling problem and results are described in detail to show how this integrated approach works.

Automatic safety analysis of computer-controlled plants

Abstract The paper describes an approach to apply the formal technique of model checking to the verification of logic controllers within the safety analysis of processing plants. In order to investigate plant safety in an early design phase in which only basic information is available, we set up plant and controller models in a qualitative and modular fashion. In a first step, the computer-controlled plant is partitioned into functional units, named modules , and the communication between different modules is represented graphically in a so-called process control event diagram (PCED). The PCED can be transformed into a formal model in which the behaviour of each module is described in terms of logical expressions for the modules’ input, state and output variables. Based on the formal model, the method of model checking can be applied to determine algorithmically whether the system fulfils a set of given safety requirements. Specifically, we use the tool symbolic model verifier (SMV) to determine whether the plant can reach states that are, in some sense, critical for the plant operation. The whole approach is illustrated by application to an industrial computer-controlled tube reactor.

The application of active databases to the problems of human error in industry

Abstract Although the general level of safety in the process industries is high a class of ‘human error’ has remained largely unaffected by engineering and regulatory advance in the industry and continues to recur. Experience is lost by industry and reports of industrial incidents are frequently inaccessible. Conventional computer database techniques are often inefficient to deal with this growing mass of data and a novel Active Database System (ADB) has been developed by Loughborough University to address this need. The ADB organises information in a novel manner using a series of loosely linked classification hierarchies, which collectively form a domain description of the chemical industrial workplace. This taxonomy has noted advantages over more traditional organisational structures. It guides both initial indexing and report retrieval. The ADB differs from other systems by being linked with other computer applications already in use by or of use to industry such as computer aided design applications or computerised Permit to Work systems. Although these systems have individual, stand-alone utility, a high degree of synergy exists making the integrated package more useful than the sum of its parts.

Hazid, A Computer Aid for Hazard Identification: 4. Learning Set, Main Study System, Output Quality and Validation Trials

The hazard and operability, or HAZOP, study is a prime method for the identification of hazards on process plants. This is the fourth in a series of papers which describe progress in the emulation of hazard identification in the style of HAZOP. The work reported is embodied in a computer aid for hazard identification, or HAZOP emulator, HAZID. The HAZID code is one of a suite of codes developed as part of the STOPHAZ project. The present paper describes the learning set of case study plants and the main case study system, used to improve the HAZID models by providing feedback on weak areas of the unit and fluid models. It also discusses the issues of correctness, completeness and conciseness in connection with output quality from HAZOP emulation. A test set of case studies were used to validate performance—the results of the evaluation of HAZID using these case studies are also discussed. Companion papers describe: an overview of HAZID, with an account of HAZOP and HAZOP emulation, and of the issues underlying it, the structure of HAZID and the associated tools in the STOPHAZ package; the unit model system; the fluid model system and the evaluation of consequences;some development topics. Conclusions from the work are given at the close of the final paper.