- following models have been developed, each for a specific purpose and with spe- cific expected results, either to validate the developed theory on engineering design integrity or to evaluate and verify the design integrity of critical combinations and complex integrations of systems and equipment.. - RAMS analysis modelling This was applied to validate the developed theory on the determination of the integrity of engineering design. - This computer model was applied to a recently constructed engineering design of an environmental plant for the recovery of sulphur dioxide emissions from a nickel smelter to produce sulphuric acid.. - The models were used to evaluate and verify the pro- cess design integrity of critical combinations and complex integrations of systems and related equipment, for schematic and detail engineering designs. - Simulation modelling for design verification is common to most engineering de- signs, particularly in the application of simulating outcomes during the preliminary design phase. - Dynamic simulation models are also used for design verification dur- ing the detail design phase but not to the extent of determining outcomes, as the level of complexity of the simulation models (and, therefore, the extent of data analysis of the simulation results) varies in accordance with the level of detail of the design.. - At the higher systems level, typical of preliminary designs, dynamic simulation of the behaviour of exogenous, endogenous and status variables is both feasible and applicable. - Mathematical modelling Modelling in the form of developed optimisation algo- rithms (OAs) of process design integrity was applied in predicting, assessing and evaluating reliability, availability, maintainability and safety requirements for the complex integration of process systems. - Artificial intelligence-based (AIB) modelling This includes new artificial intel- ligence (AI) modelling techniques, such as knowledge-based expert systems within a blackboard model, which have been applied in the development of intelligent com- puter automated methodology for determining the integrity of engineering design.. - The AIB model provides a novel concept of automated continual design reviews throughout the engineering design process on the basis of concurrent design in an integrated collaborative engineering design environment. - The measures of integrity are based on the developed theory for predicting, assessing and evaluating reliability, availability, maintainability and safety require- ments for complex integrations of engineering process systems. - The relevant de- sign criteria pertaining to each level of a systems hierarchy of the engineering de- signs are incorporated in an all-encompassing blackboard model. - The blackboard model incorporates multiple, diverse program modules, called knowledge sources (in knowledge-based expert systems), which cooperate in solving design problems such as determining the integrity of the designs. - Such information includes the RAMS analysis data, results from the op- timisation algorithms, and compliance to specific design criteria, relevant to each level of systems hierarchy of the designs. - In this manner, integrated systems and related equipment are continually evaluated for design compatibility and integrity throughout the engineering design process, particularly where designs of large sys- tems give rise to design complexity and consequent high risk of design integrity.. - Contribution of research in integrity of engineering design Many of the meth- ods covered in this handbook have already been thoroughly explored by other researchers in the various fields of reliability, availability, maintainability and safe- ty, though more in the field of engineering processes than of engineering de- sign. - What makes this handbook unique is the combination of practical methods with techniques in probability and possibility modelling, mathematical algorithmic modelling, evolutionary algorithmic modelling, symbolic logic modelling, artificial intelligence modelling, and object oriented computer modelling, in a structured ap- proach to determining the integrity of engineering design. - This endeavour has en- compassed not only a depth of research into these various methods and techniques but also a breadth of research into the concept of integrity in engineering design.. - Such breadth is represented by the combined topics of reliability and performance, availability and maintainability, and safety and risk, in an overall concept of the integrity of engineering design—which has been practically segmented into three progressive phases, i.e. - Thus, a matrix combination of the topics has been considered in each of the three phases—a total of 18 design methodology aspects for consideration—hence, the voluminous content of this handbook. - Such a comprehensive combination of depth and breadth of research resulted in the conclusion that certain methods and tech- niques are more applicable to specific phases of the engineering design process, as indicated in the theoretical overview and analytic development of each of the topics.. - Taking all these design methodology aspects into consideration, the research presented in this hand- book can rightfully claim uniqueness in both integrative modelling and practical application in determining the integrity of process engineering design. - A practical industry-based outcome is given in the establishment of an intelligent computer au- tomated methodology for determining integrity of engineering design, particularly for design reviews at the various progressive phases of the design process, namely conceptual, preliminary and detail engineering design. - The overall value of such methodology is in the enhancement of design review methods for future engineer- ing projects.. - The scope of research for this handbook necessitated an in-depth coverage of the relevant theory underlying the approach to determining the integrity of engineer- ing design, as well as an overall combination of the topics that would constitute such a methodology. - Additionally, a listing of books on the scope of the theory covered is given in Appendix B. - However, besides these methods and techniques and theory, certain essential preliminaries used by design engineers in determining the integrity of engineering design include activities such as:. - Quantification of engineering design criteria. - Determination of failure consequences. - Determination of failure effects. - The methodology researched in this handbook, in which engineering design problems are formulated to achieve optimal integrity, has been extended to accommodate its use in conceptual and preliminary or schematic design in which most of the design’s components have not yet been precisely defined in terms of their final configuration and functional performance.. - 1.1.2 Designing for Reliability, Availability, Maintainability and Safety. - The fundamental understanding of the concepts of reliability, availability and main- tainability (and, to a large extent, an empirical understanding of safety) has in the main dealt with statistical techniques for the measure and/or estimation of various parameters related to each of these concepts, based on obtained data. - Censored data arise from the cessation of experimental ob- servations prior to a final conclusion of the results. - The usual meaning of the term reliability is understood to be ‘the probability of performing successfully’. - Since such results can vary, the estimated reliability can be different from one set of data to another, even if there are no substantial changes in the physical characteristics of the item being assessed.. - Thus, associated with the reliability estimate, there is also a measure of the sig- nificance or accuracy of the estimate, termed the ‘confidence level’. - This means that the data can be interpreted by one or other mathematical formula representing a specific statistical probability distribution that belongs to a family of distributions differing from one another only in the values of their parameters.. - Both availability and maintainability have the dimensions of a probability distribution in the range zero to one, and are based upon time-dependent phenom- ena. - success or failure in the function of an item. - They do not consider situations in which there are some means of backup for a failed item, either in the form of re- placement, or in the form of restoration, or which include multiple failures with standby reliability, i.e. - Therefore, assigning confidence levels to values of availability cannot be done parametrically, and a technique such as Monte Carlo simulation is employed, based upon the estimated values of the parameters of time-to-failure and time-to- repair distributions. - When such distributions are exponential, they can be reviewed in a Bayesian framework so that not only the time period to specific events is sim- ulated but also the values of the parameters. - Maintainability is concerned with only one random variable—the repair time for a failed system. - In both cases, if the time to an event of failure is governed by either a parametric, Poisson or Weibull distribution, then the confidence levels of the estimates can also be assigned parametrically.. - However, in designing for reliability, availability and maintainability, it is more often the case that the measure and/or estimation of various parameters related to each of these concepts is not based on obtained data. - This poses a severe problem for engineering de- sign analysis in determining the integrity of the design, in that the analysis cannot be quantitative. - Furthermore, the complexity arising from an integration of engineering systems and their interactions makes it somewhat impossible to gather meaningful statistical data that could allow for the use of objective probabilities in the analysis.. - Other acceptable methods must be sought to determine the integrity of engineer- ing design in the situation where data are not available or not meaningful. - These methods are to be found in a qualitative approach to engineering design analysis.. - A qualitative analysis of the integrity of engineering design would need to incorpo- rate qualitative concepts such as uncertainty and incompleteness. - Uncertainty and incompleteness are inherent to engineering design analysis, whereby uncertainty, arising from a complex integration of systems, can best be expressed in qualitative terms, necessitating the results to be presented in the same qualitative measures. - The methodology for determining the integrity of engineering de- sign is thus not solely a consideration of the fundamental quantitative measures of engineering design analysis based on probability theory but also consideration of. - a) Designing for Reliability. - In an elementary process, performance may be measured in terms of input, through- put and output quantities, whereas reliability is generally described in terms of the probability of failure or a mean time to failure of equipment (i.e. - This distinction is, however, not very useful in engineering design because it omits the assessment of system reliability from preliminary design con- siderations, leaving the task of evaluating equipment reliability during detail design, when most equipment items have already been specified. - System reliability can be defined as “the probability that a system will perform a speci- fied function within prescribed limits, under given environmental conditions, for a specified time”.. - An important part of the definition of system reliability is the ability to perform within prescribed limits. - The constraints are identified by consid- ering the effects of failure of each identified performance variable. - Designing for reliability at the systems level includes all aspects of the ability of a system to perform. - When assemblies are configured together in a system, the system gains a collective identity with multiple functions, each function identified by the collective result of the duties of each assembly. - Performance is the ability of such an assembly of components to carry out its duties, while reliability at the component level is determined by the ability of each of the components to resist failure. - Unacceptable performance is considered from the point of view of the assembly not being able to meet a specific performance variable or designated duty, by an evaluation of the effects of failure of the inherent. - components on the duties of the assembly. - Designing for reliability at the prelim- inary design stage would be to maximise the reliability of a system by ensuring that there are no ‘weak links’ (i.e. - assemblies) resulting in failure of the system to perform its required functions.. - Similarly, designing for reliability at the detail design stage would be to max- imise the reliability of an assembly by ensuring that there are no ‘weak links’ (i.e.. - components) resulting in failure of the assembly to perform its required duties.. - It is incorrect to describe a pump as ‘reliable’ if the rates of failure of its components are low, yet it does not perform a specific duty required of it.. - Similarly, in a hydraulic system, a particular assembly may appear to be ‘reli- able’ if the rates of failure of its components are low, yet it may fail to perform a specific duty required of it. - The intention of designing for reliability is thus to design integrated systems with assemblies that effectively fulfil all their required duties.. - However, because many different constraints defined in different units may apply to the overall per- formance of the system, a method of data point generation based on the limits of non-dimensional performance measures allows design for reliability to be quanti- fied.. - The choice of limits of performance for such an approach is generally made with respect to the consequences of failure and reliability expectations. - If the conse- quences of failure are high, then limits of acceptable performance with high safety margins that are well clear of failure criteria are chosen. - The most significant advantage of this method is that, be- sides not having to rely on the propagation of single estimated values of failure data, it does not have to rely on the determination of single values of maximum and minimum acceptable limits of performance for each criterion. - In addition, the concept of uncertainty in design integrity, both in technology as well as in the complex integration of multiple systems of large engineering pro- cesses, is considered through the application of uncertainty calculus utilising fuzzy sets and possibility theory. - Furthermore, the application of uncertainty in failure mode effects and criticality analyses (FMECAs) describes the impact of possible faults that could arise from the complexity of process engineering systems, and forms an essential portion of knowledge gathered during the schematic design phase of the engineering design process.. - In the case where data are sparse or non-existent for evaluat- ing the performance and reliability of engineering designs, information integration technology (IIT) is applied. - This multidisciplinary methodology is particularly con- sidered where complex integrations of engineering systems and their interactions make it difficult and even impossible to gather meaningful statistical data.. - b) Designing for Availability. - Designing for availability, as it is applied to an item of equipment, includes the aspects of utility and time. - Designing for availability is concerned with equipment usage or application over a period of time. - Availability can be simply defined as “the item’s capability of being used over a period of time”, and the measure of an item’s availability can be defined as “that period in which the item is in a usable state”. - As with designing for reliability, which includes all aspects of the ability of a system to perform, designing for availability includes reliability and maintainability consid- erations that are integrated with the performance variables related to the measures of time that are subject to equipment failure. - Designing for availability thus incor- porates an assessment of expected performance with respect to the performance measures of MTBF, MDT or MTTR, in relation to the performance capabilities of the equipment. - In the case of MTBF and MTTR, there are no limits of capability.. - Instead, prediction of the performance of equipment considers the effects of failure for each of the measures of MTBF and MTTR.. - System availability implies the ability to perform within prescribed limits quan- tified by defining constraints on acceptable performance that is identified by consid- ering the consequences of failure of each identified performance variable. - Designing for availability during the preliminary or schematic design phase of the engineering. - Petri nets are useful for modelling complex systems in the context of sys- tems performance, in designing for availability subject to preventive maintenance strategies that include complex interactions such as component renewal. - Such inter- actions are time related and dependent upon component age and estimated residual life of the components.. - c) Designing for Maintainability. - Maintainability is that aspect of maintenance that takes downtime into account, and can be defined as “the probability that a failed item can be restored to an operational effective condition within a given period of time”. - Corrective maintenance action is the action to rectify or set right defects in the item’s operational and physical conditions, on which its functions depend, in ac- cordance with a standard. - This repair action is in fact determined by the mean time to repair (MTTR), which is a measure of the performance of maintainability.. - Maintainability is a measure of the repairable condition of an item that is deter- mined by the mean time to repair (MTTR), established through corrective main- tenance action.. - Designing for maintainability fundamentally makes use of maintainability predic- tion techniques as well as specific quantitative maintainability analysis models re- lating to the operational requirements of the design. - Maintainability predictions of the operational requirements of a design during the conceptual design phase can aid in design decisions where several design options need to be considered. - Designing for maintainability basically entails a con- sideration of design criteria such as visibility, accessibility, testability, repairability and inter-changeability. - Designing for maintainability at the systems level requires an evaluation of the visibility, accessibility and repairability of the system’s equipment in the event of failure
Xem thử không khả dụng, vui lòng xem tại trang nguồn hoặc xem
Tóm tắt