Handbook of Reliability, Availability, Maintainability and Safety in Engineering Design - Part 36 pot

4.2 Theoretical Overview of Availability and Maintainability in Engineering Design 333 To obtain a reasonable measure of the process capability, the length of the time frame should be chosen such that it is long enough to reflect all the substantial sources of variation in the process. Defining the sampling method or procedure is also important. The pilot process output should be sampled in such a way that a ‘fair’ representation is obtained of the process over the chosen time frame. For capability calculations, it is not always necessary for the samples to be collected in subgroups. However, sub-grouping of the pilot process d ata can also be used to create control charts that may be helpful in understanding a particular process characteristic. Altering the process view can substantially change the conclusions about the process capability. As a r esult, specific guidelines regarding the time frame, and the sampling method used to collect the pilot process data necessary for calculat- ing capability, are essential. Another important issue related to the p rocess view is the number of data points used in the estimation. P pk is an estimate of the process capability and, thus, even if the process is unchanged, taking another sample and recalculating the index is unlikely to yield precisely the same result. The amount of uncertainty is based on both the properties of the process and the number of data ob- servations used to calculate the capability index. Larger sample sizes provide more information and, thus, tend to lead to better estimates of the process capability. A further important aspect in considering process capability as an indicator in designing for availability is process stability. A process is considered stable if all the points on its X and R control charts fall within the design control limits, and there are no apparent deviation patterns. Th e stability of a process is a n important property in designing for availability because, if the process design is considered stable, it is likely to also be stable in its installation and in the future, assuming that no major changes occur. Thus, the total output of a stable process is, in some sense, predictable. If the output of a process is considered stable, then the process’ capability is predictable, from design to manufacture through to installation and/or construction. On the other hand, if the process output is not deemed to be stable, it might still be possible that over time the process capability index can appear to be stable, depending on the complexity of the process and/or the complex integra- tion of the relevant process systems. The predictability of process capability can be obtained by considering the performance of the process in terms of its process ca- pability over time. If the pilot pro cess capability values exhibit a stable pattern, then there would be some confidence predicting the installed process capability indices, which affects the consequences of using the capability ind ices of P pk and C pk .If the process is stable, then C pk is approximately equal to P pk , since a stable process has little variability. Thus, if the process is stable, it does not matter much which measure is used (although P pk is preferred). On the other hand, if the process is unstable, there will be substantial variability between the data subgroups, and C pk is thus not equal to P pk . In the case of process instability, C pk will overestimate the process capability, since it does not include variability. The same principle applies if the process is unstable and yet predictable. As a result, in all situations, P pk provides a better measure of the process capability than does C pk . Thus, in the development of intelligent computer automated methodology for determining the integrity of engineering design, particularly through the use of 334 4 Availability and Maintainability in Engineering Design a blackboard model to provide for automated continual design reviews with respect to designing for availability, such reviewsinevitably need to include capabilitymod- els of each process system. Each cap ability model includes a combination of declar- ative design rules and constraints, design criteria documentation, and process simu- lation results. The design rules represent constraints that apply to the design’s mate- rials and processes associated with each p rocess capability model, such as process and functional characteristics, geometric symmetries, and expressions constraining the parameters of specific system features. Process simulations take as input the geometric model of a design or partial design, and return estimates on the process and functional characteristics, or pro- vide a graphical display of the characteristics and their effects. For the purpose of ensuring design for manufacturability, a set of design ru les that will ensure easy manufacturability is paramount. Representations of process-derived geometric con- straints provide a way of assuring man ufacturability while maintaining the neces- sary distinction between the representation of the design and the description of the processes used to manufacture it. The neutral descriptions of these constraints also enable their use for constraint propagation in qualitative reasoning systems such as knowledge-based expert systems. b) Process Characteristics Process characteristics include the following measures: • process capacity, • process input, • process throughput, • process output, • process quality. Process capacity: Capacity can be defined as “holding or receiving ability”. The capacity of an engineering process n ormally represents a limit on the maxi- mum holding ability of the process. In this context, process capacity can be defined as “the ability of a series of operations to receive and/or hold the result or product inherent to the process”. Process capacity has thus to do with receiving an input, and a system’s ability to hold or retain an operational throughput as a result of delivering an output, and should not be confused with the specific measures of a system’s input, throughputor output. Process capacity is the maximum amount of material or product in process. Process capacity decisions are perhaps the most fundamental of all conceptual engi- neering design considerations. One reason for the importance of capacity decisions relates to the impact on the ability of the process to meet future demands—capacity essentially limits the rate of possible output. A second reason for the importance of process capacity decisions is the initial cost involved. Capacity is usually a major determinant of a design’s manufactur- ing a nd in stallation costs. Ano ther reason for the importance of process capacity 4.2 Theoretical Overview of Availability and Maintainability in Engineering Design 335 decisions stems from the long-term commitment of resources required in the oper- ation of the installed design, and the fact that once installed, it may be difficult to modify the process without incurring major costs. The term process capacity generally refers to an upper limit on the rate of pro- cess output. Even though this seems to b e simple enough, there are difficulties in actually measuring process capacity. These difficulties arise because of different in- terpretations of the term process capacity, and problems with identifying suitable measures. Underlying these interpretations, though, is the single fact that process capacity reflects the availability of process resources. There are thus three different definitions of process capacity that are applicable to availability in engineering design: • Design capacity (C d ): the maximum ability of a series of operations to receive and/or hold the result or product inherent to the process. • Effective capacity (C e ): the ability of a series of operations to receive and/or hold the result or product inherent to the process, given a specific product mix, production schedule, maintenance, and quality constraints. • Rated capacity (C r ): the throughput actually achieved from operational con- straints placed upon the ability of a series of operations to receive and/or hold the result or product inherent to the process. Rated capacity is maximum throughput. Measuring process capacity Process capacity can beexpressed in terms ofoutputs or inputs, though no single capacity measure is universally applicable. Expressing process capacity in terms of output measures is the usual choice for line flow pro- cesses. However, product mix becomes an issue when the output is not uniform in work content. Expressing process capacity in terms of input measures is normally used for flexible flow processes where process output varies in work content, and a measure of total production or units produced becomes meaningless. Maximum process capacity can be measured in terms of the average output rate and the average utilisation rate expressed as a percentage Maximum Capacity (C max )= Average output rate Average utilisation/100 . (4.20) Process input (I p ): Process input is the quan tity or volume of process material th at enters the system o r equipmentover a period of time in accordance with the system’s operationaltime. Production input in continuous processes is the quantity or volume of process material that can enter the system or equipment according to its process capacity. Maximum input is the maximum ability to receive and/or hold the result or product inherent to the process, i.e. design capacity. Process throughput (T p ): Process throughput has to do with quantities of mate- rial entering and leaving the system process over a period of processing time. With continuous processes, throughput is the qua ntity of material entering and leaving the process in a continuous flow. The material or product in process, at rated ca- pacity, is the difference between the input and output at any specific point in time. The throughput rate is eq uivalent to the rated capacity per unit of time. Process 336 4 Availability and Maintainability in Engineering Design throughput rate is indicative of the capability of the process to achieve the de- sired result or output. From Little’s law (Little 1961), the formula for the relation of throughput, cycle time and work in progress in any production line is given as Production throughput (T prod )= Work in progress Cycle time . (4.21) In the context of discrete industrial processes, work in progress is synonymous to the m aterial or product in process. Thus Process throughput (T D proc )= Material in progress Cycle time (4.22) where cycle time in discrete industrial processes = processing time + added time due to operational constraints and inspection. Process throughput of a continuous process system can be defined as “the ratio of a system’s material in process over a period of processing time” Process throughput (T C proc )= Material in progress Processing time (4.23) = Rated capacity (C r ) . Process output (O p ): Output can be defined as “the quantity produced or yielded”. Process output can be defined as “the quantityof product,or yield of a production process”. Process output has to d o with yield quantities o f product or material from the production process. The relationship between process throughput and process output is given by the following Process output (O p )=Process throughput (T p ) (4.24) ×Yield percentage (Y%) Utilising the previous formula for rated capacity as maximum throughput,therela- tionship between output and yield in accordance with a process plant’s rated capac- ity gives the following Process output (O p )=Rated capacity (C r ) (4.25) ×Yield percentage (Y%) Process or product yield Yield can be defined as “the amount produced or the output result”. Product yield in quality terms (without reject product) is the throughput multi- plied by the percentage of successful output result (yield percentage) Process yield (Y p )=Process throughput (T p ) ×Yield percentage (Y%) (4.26) = Process output (O p ) 4.2 Theoretical Overview of Availability and Maintainability in Engineering Design 337 c) Functional Effectiveness Functional effectiveness in engineering processes indicates the results produced. It represents functional characteristics of th e process, such as p rocess efficiency, util- isation and productivity. Availability in engineering d esign, particularly in produc- tion processes, is often looked upon as a functional characteristic synonymous to productivity in that it relates process output to input. Process effectiveness in itself is an indicationof the design’smanufacturedand/or installed accomplishment against the d esign’s intended capability.Process effective- ness is a ratio of process results (i.e. actual output) to p rocess cap ability (i.e. design output) Process Effectiveness (W p )= Actual output Design output . (4.27) Process efficiency is the ratio of process output achieved through the process throughput (or, in certain cases, process input). In order to understand the concept of efficiency correctly, and not confuse it with the concept of effectiveness, it is n ec- essary to consider these definitions with regard to related terminology. Inasmuch as output is defined as the quantity produced or yielded, so can effi- ciency be defined as “the capability of producing or yielding an output quantity”. In fact, it is this capability of output quantity that forms the basis of efficiency mea- surement. Efficiency measurement is the measurement of productive capability. Efficiency measuremen t of en gineering processes is thus the measure of the capability of pro- ducing or yielding a product. It is the measure of the capability of output quantity. Efficiency measurement of a process, as a ratio, must therefore include output quan- tity compared to some or other production parameter of the equipment in o rder to reflect its capability of outputquantity.As this productivecapabilitylogically relates directly to the amountthat can be put througha process, it is conclusive that the pro- duction parameter must be process throughput. Efficiency measurement o f an engi- neering process is thus a comparison of the outputquantityto its process throughput. Thus Process efficiency (X p )= Process output Process throughput (4.28) = Process throughput×Yield percentage Process throughput = Yield percentage (Y%) The measure of efficiency must not be confused with the measure of productivity, which is the ratio of output compared to input. Productivity is the “ratio of process output to process input” Productivity (Z)= Process output Process input (4.29) = Process throughput×Yield percentage Process input 338 4 Availability and Maintainability in Engineering Design Process utilisation Process utilisation is the ratio of process output to the con- strained ability to receive and/or hold the result or product inherent to the process (i.e. rated capacity) Process utilisation (U p )= Process output Rated capacity (4.30) Functional effectiveness in engineering processes represents the functional charac- teristics of a process, such as efficiency, productivity and utilisation. These char- acteristics relate process output to throughput, output to input, and output to ca- pacity respectfully. Availability in engineering design is thus considered from the perspective of these functional characteristics, and designing for availability, partic- ularly engineering p rocess availability, considers measurements of process through- put, output, input and capacity. d) Mathematical Modelling For each process system, there is a set of performance measures that require partic- ular attention in design. Mathematical models for expressing systems p rocess char- acteristics, and functional effectiveness for both discrete and continuous process systems involve respectively summation and integration of their conjunct variables over time. These models serve as useful indicators in designing for availability,and adequately represent performance measures of each system that can be described in matrix form in a parameter profile matrix (Thompson et al. 1998): Discrete process throughput  T D proc  = P ∑ p=1 (M/t)p 1 < p < P . (4.31) Continuous process throughput  T C proc  = T  t (M t /t) dt 0 < t < T (4.32)  T C proc  max =(C r ) Process output  O p  = T  t (M t /t)(Y t )dt (4.33)  O p  max =(C r ) ×(Y%) 4.2 Theoretical Overview of Availability and Maintainability in Engineering Design 339 Process effectiveness  W p  = T  t (M t /t)(Y t /O d ) dt (4.34)  W p  max =(O p ) max /O d Process efficiency (X p )= T  t (M t /t)  Y t /T C proc  dt (4.35) (X p )=(Y%) Productivity (Z)= T  t (M t /t)  Y t /I p t  dt (4.36) (Z)=  O p   I p  Process utilisation  U p  = T  t (M t /t)(Y t /C r ) dt (4.37)  U p  =  O p  (C r ) where: M t = material in process in time t M t /t = process flow rate or mass-flow rate I p = process input Y t = yield O d = design output C d = design capacity C r = rated capacity O p t = process output in time t (O p ) max = maximum process output. In general continuous flow processes, there are certain governing equations of flow, where the design process flow rate or themass-flow rate M t /t (i.e. throughput,which is a pivotal parameter in the performance measures for expressing systems process characteristics) is the base measure of fundamental fluid flow. The amount of fluid 340 4 Availability and Maintainability in Engineering Design (or material) flowing through a specified cross section is referredto as the volumetric flow rate. Let W = M t /t be the total mass-flow rate of fluid flowing through a specified cross section. Then V = W/ ρ (m 3 /h) (4.38) where: V = volumetric flow rate ρ = fluid density. The average linear velocity of flow is the ratio of the volumetr ic flow rate to the cross-sectional flow area, as given by the following relationship ˆw = V/F (m/h) (4.39) where: ˆw = average flow velocity F = cross-sectional flow area. Mass velocity can be expressed as the average velocity modified by the specific weight of the fluid, which is the fluid’s specific gravity G = ˆw· γ (4.40) where: G = fluid mass velocity γ = fluid specific gravity. For a continuous flow process under steady-state conditions, the mass-flow rate M t /t,orW, must be the same at any section within the process. This is the prin- ciple of mass-flow balance W 1 = W 2 = W 3 = etc. (4.41) The mass-flow balance is a statement of continuity, which can also be written as F 1 G 1 = F 2 G 2 = F 3 G 3 = etc. (4.42) where: F = cross-sectional flow area G = fluid mass velocity and: ρ = fluid density γ = fluid specific gravity ρ / γ = constant. 4.2 Theoretical Overview of Availability and Maintainability in Engineering Design 341 Without going into the depths of fluid mechanics and hydraulics, which is not rel- evant to the objectives of this handbook, the nature of general flow regimes needs to be considered in order to address not only the principle o f mass-flow balance in continuous flow processes but their total energy balance as well, so that these mea- sures can be used in determining system performance characteristics that may serve as useful indicators in designing for availability without having to formulate the specific operational variables of each individual system. This is best done through simulation, which is considered more closely in the next section on analytic devel- opment. There are fundamentally three general flow regimes in continuous flow pro- cesses: laminar flow, transition flow and turbulent flow. The laminar flow regime o ccurs at relatively low fluid velocities, providing a smooth flow pattern with no or very little mixing of the fluid particles. Transi- tion flow denotes the onset of turbulence. In a turbulent flow regime, fluid velocities are higher, and an unstable pattern within the mass flow is observed in which eddy current forces move at all angles to the axis of normal flow. The dependency of a particular flow regime is denoted by the dimensionless Reynolds number whereby a critical Reynolds number indicates the transition from one flow regime to another. For instance, if the Reynolds number for flow in a straight circular pipe is less than 2,100, the flow is laminar. When the Reynolds number exceeds 4,000, the flow is turbulent. Flow between these two critical num- bers is transitional. The mathematical model for the Reynolds number is g iven by the following re- lationships Re = W ·D/ ν = ˆw·D· ρ / μ = W ·D/ μ (4.43) where: Re = Reynolds number W = mass-flow rate D = system or tube (pipe) diameter ν = kinematic viscosity ν = μ / ρ ˆw = average flow velocity ρ = fluid density μ = dynamic viscosity. Specific mathematical models for volumetric flow rates, V, and average flow veloc- ities, ˆw, for laminar flows in a variety of systems are available in determining the Reynolds number. In considering the total energy balance, the flow energy input of a continuous flow process is the sum of the kinetic energy, E k , the potential energy, E p ,thevol- umetric energy, E v , and the internal energy, E i . Any disruption in one or another of these energies in the total energy balance is an indication of degradation in the performance or operability of the process and, thus, these are important criteria in its engineering design. 342 4 Availability and Maintainability in Engineering Design The availability of the process or system is concerned with expected system per- formance over a period of expected operational time. The prediction of inherent availability of systems is based upon a prognosis of systems performance and sys- tems operability under conditions subject to various performance criteria,suchas mass-flow balance and total energy balance. Inclusive of any heat input from heat exchangers, or mechanical work derived from pumping, the total energy balance of a continuous process flow consists of the four energies E k , E p , E v and E i , whereby the total energy balance can be formulated as follows E k 1 + E p 1 + E v 1 + E i 1 = E k 2 + E p 2 + E v 2 + E i 2 (4.44) The kinetic energy, E k , is a function of the fluid mass and the fluid’s linear velocity: E k 1 = ˆw 2 1 /2g α E k 2 = ˆw 2 2 /2g α where: α = correction coefficient and, for turbulent flow, α = 1. The potential energy, E p , is a function of the weight, Z,ofthefluid: E p 1 = Z 1 E p 2 = Z 2 The volumetric energy, E v , under pressure P, is equivalent to the energy required to hold volume v at that pressure: E v 1 = P 1 v 1 E v 2 = P 2 v 2 The internal energy, E i , is a thermodynamic property of the flow system, with refer- ence state energies, E 1 , E 2 , which on the input side is a function of heat input from heat exchangers, H e , and mechanical work from pumping, M e , approximated by the enthalpies i 1 and i 2 : E i 1 = state E 1 = H e + M e E i 2 = state E 2 i 1 = E 1 + P 1 v 1 i 2 = E 2 + P 2 v 2 The total energy balance can now be formulated as follows (Cheremisinoff 1984): ˆw 2 1 /2g α + Z 1 + P 1 v 1 + H e + M e = ˆw 2 2 /2g α + Z 2 + P 2 v 2 + E 2 (4.45) ˆw 2 1 /2g α + Z 1 + H e + M e = ˆw 2 2 /2g α + Z 2 +(i 2 −i 1 ) . for determining the integrity of engineering design, particularly through the use of 334 4 Availability and Maintainability in Engineering Design a blackboard model to provide for automated continual design. determinant of a design s manufactur- ing a nd in stallation costs. Ano ther reason for the importance of process capacity 4.2 Theoretical Overview of Availability and Maintainability in Engineering. the input and output at any specific point in time. The throughput rate is eq uivalent to the rated capacity per unit of time. Process 336 4 Availability and Maintainability in Engineering Design throughput