The availability discipline is established in the plant as a living process. Availability management will become part of total plant functioning. Otherwise, the ability of the plant to perform according to the most profitable availability scheme will generally decline over time. This chapter explores the role of the availability discipline in corporate, operating company and plant management. Subsequent chapters explore the role in detail as a set of work and decision processes.
This exploration will reveal that it is a mistake to view availability management and its maintenance operations only in the context of plant functioning and improvement. Instead, availability management and its living processes are a substantial, natural and integral part of all classic management cycles. These cycles occur throughout the corporate, operating company, and plant organizations. All three are empowered by availability management to more closely achieve their full potential in creation of income and maximum use of assets.
This empowerment is made possible by the availability engineering work products of the previous design phases. There are now findings, tools, work processes and functions in place to serve the plant throughout its producing life.
Writing should be an exploration. Discoveries occur as a writer carefully develops the logic that connects the ends to the middle. That was very much the objective and the case for writing this part of the book.
This exploration begins by finding a basis to describe the nature, needs, and business processes of the plant’s productive life. This description must also regard the plant as part of a larger production and business system.
Thus, the first challenge was to step beyond merely describing the discipline in the plant’s productive cycles. The answer would have been limited to maintenance operations and evaluating, improving, and adjusting availability performance.
Therefore, the points that are explored are the following:
This chapter identifies and introduces those cycles. It then explores the role of availability engineering and management in these cycles. The next three chapters translate those roles to availability management processes within the classic cycles.
Classic cycles of management can be distinguished when the plant is viewed within the owner’s larger business enterprise. This begin with strategic cycles and continue through day-to-day online production cycles and subsequent performance evaluation. The entire chain includes cycles of design, construction, and startup. All occur both laterally and vertically along the corporate, operating company, and plant organizations.
More specifically, the following management cycles will be introduced:
These management or business process cycles that occur repeatedly throughout the plant’s producing lifetime are not a matter of beginning with the strategic cycle (TO1) and passing through each to the end of the overall production and business system operations management cycle and then starting over. Instead, the plant’s entire productive life will be cycles of change in functioning or design. Each will reflect decisions by corporate, operating company, and plant management.
Figure 17-1 shows that the production operations management cycles of the commercial production phase fall within the following clusters.
The production and pertinent business systems operations management cycles are coded as “TO” in Figure 17-1. This is to denote traditional production operation management cycles. They are described in the following sections.
Long-term vision. The first cluster of cycles has a long-term vision. It sets the direction and capability of the organization. Its cycles are
These cycles are concerned with the directions that can be taken, the knowledge and technologies that will be used to perpeptuate or fulfill those decisions, and the development of the system to incorporate those technologies. Each cycle of the cluster can be triggered by the feedback from the other two clusters.
Middle-term planning. The second cluster has a middle-term orientation, which pieces together the organization’s resources to perform short-and middle-term production management activities. The aggregate planning and operating budget cycles are concerned with matching the organization’s production capacity to short- and middle-term demand in the most profitable manner. The cluster will also provide influential feedback to the previous cluster.
Short-term planning and action cycles. A third cluster is concerned with using and fine-tuning production and organizational plans and elements. The production planning, production, and maintenance operation cycles are at the heart of that purpose. Ultimately, the performance evaluation cycle will assess how well the core cycles of production actually fit with what the strategic and middle-term cluster had intended. Therefore, the cluster provides feedback to the other two.
Each cycle within a cluster is related to other cycles in its cluster. It is also related to those in other clusters. When one cycle arrives at a disequilibrium, others are subject to activation. Which cycles respond is a function of the nature of disequilibrium. Disequilibrium is defined as follows:
Therefore, a cycle can trigger others. Initially, the response may be an adjustment. Eventually, a small to large cycle of design, construction, and associated startup will occur.
The plant may be just one in a larger production system. These same cycles in related upstream, downstream, or parallel production facilities can trigger a cycle in a subject plant. The reverse is also true.
Corporate, operating company, and plant management must develop long-term strategies. This is typically an annual cycle in modern-day business management.
There are hierarchies of strategy parallel to the nature of corporate, operating company and plant management. Each has a different focus. Combined, they form a single holistic strategy for the total organization. The scope of each hierarchial level is as follows:
The strategic cycle has two stages. The first is analyses; the second is strategic decisions. The decisions include many possibilities. Some are as follows:
Availability engineering and management is critical to all of these decisions. The discipline has the following relationships:
The strategic cycle includes long-range financial planning. This is the analysis of the consequences of candidate and chosen strategies on financial statements for many years to come.
Thus, the strategic cycle will consider the owner’s long-term financial picture. This view looks at the case for “what if” the company continues as it is and assesses the financial consequence of the strategies being evaluated and considered.
Management is often regarded as having a short-term perspective. This is sometimes true. It is also because employees and the public do not often see the long-term financial analysis process in action. Instead, they observe and are more widely involved in the short-term operating budget process. Its purpose is to maximize the short-term with respect to long-term strategies and financial expectations.
Ultimately, the cycle selects strategies and prepares detailed plans for their realization. The strategy will establish the following:
Availability engineering and management has an important role in the strategic cycle. This is true across corporate, operating company and plant management. The primary nature of the contribution is as follows:
It is apparent that the strategic cycle is less effective without availability management as an organizational capability. Otherwise, a major dimension of the production system is not competently included and treated in the strategic process.
This has immense ramifications. Studies show that companies that plan do much better than those that do not. And, those that start planning in later stages do better than when they did none [Hofer and Schendel, 1978]. This suggests that the quality of the strategy process is crucial to how a company performs. The organizational capability for availability engineering and management is integral to that quality.
Research and development is a circle of discovery, learning, and application. Therefore, it leads to change as it eventually triggers and influences the other cycles. This is because it includes the following:
There is often a narrow perception of research and development as focused on products, production processes, and equipment. However, it also includes the following:
Therefore, the scope of research and development is the quest for improved overall production and business system performance. This is measured by the ability of the organization to use its scarce resources in all aspects of achieving organizational success. This long-run strategic productivity can be improved when research and development explores and develops methods applicable to:
Availability engineering and management is both a contributor and a participant in the research and development cycle. The availability-centered improvement, change and data management functions and systems are an integral part of the research and development cycle. This is because they collect and evaluate data and information from the plant’s actual production and support experience.
Living availability design treats the functioning plant as a controlled test laboratory. Thus, it provides processed and evaluated feedback to formal research and development processes.
The living availability design should be regarded as fundamental to the research and development function and its cycle.
The planning cycles for research and development activities will include the details for capitalizing on the availability-centered improvement, change and data management systems and processes.
The plans should not be just limited to the availability performance of current facilities. They must also develop reliability and maintainability experience and insights that can be drawn upon in the development of new technologies.
The aggregate planning cycle has various names. It is defined here as the cycle of matching productive capacity with forecasted demand. This match incorporates issues of current strategies, resource position, etc. The domain is the owner’s company-wide aggregate capacity to produce a product.
The cycle always exists. However, it may be hidden or so closely tied to other management cycles that it is not an obvious or even a named process. However, there is always a process with the purpose of matching productive capacity to market demand and other strategic and constraining issues. An example, is an oil and gas exploration and production organization. Aggregate planning is generally an implicit process within the production department’s field development decisions and associated operating budgets.
The aggregate planning process is generally as follows:
The aggregate planning cycle may be monthly. The planning horizon can range up to several years. As previously mentioned, the most basic objective is to match the organization’s capacity to meet demand.
This determines the planning horizon. It is important to determine when the owner’s system of plants may no longer meet its share of forecasted total market demand. This will be the point at which the plant reaches the outer limits of physically or economically feasible capacity.
The planning time-horizon should be long enough to identify this outer limit. It should allow time to begin the management cycles in the immediate-term to develop the necessary future capacity.
There are several implications in the description of aggregate planning. Large operating companies will have multiple production trains, plants and locations for producing the same product. Thus, the objective of aggregate planning at the operating-company level is to optimize production performance and economics for a group of plants.
The production functioning of each plant may be suboptimized. Thus, the capacity to be economically and managerially flexible is a fundamental issue during the commercial production life of a single plant. This is because of the opportunity it provides for formulating advantageous aggregate plans.
Availability engineering and management is fundamental to aggregate planning. This is especially so with regard to the concept of living availability design functions and systems.
Three measures of a successful solution.. There are three fundamental measures of a successful solution to aggregate planning. They are as follows:
Availability engineering and management is strongly associated with the first and third goals. The living availability design process is challenged to squeeze productive capacity out of a plant in accordance with these criteria.
Outer limits of feasible performance At some point in the plant’s life, no possibilities will remain to hold the cost structure of the availability scheme in the economic valley of Figure 1-10. At a later point, the cost of incremental availability can no longer even be made less than the incremental production value it creates. At an even later point, it will no longer be possible to increase availability performance regardless of spending for field and functional activities.
The alternative is to increase production capacity with capital-based strategies. A possibility is to debottleneck the plant. A greater strategy is a plant addition or a new plant.
The living design systems and availability management functions are basic to these issues since they are concerned with determining a profitable and possible availability scheme. They will also search for the point where there are no longer working capital solutions (operational availability) to availability in productive capacity.
Capacity for dynamic aggregate performance. The living availability design has another role in the aggregate planning cycle. As business cycles oscillate, there will be times that less, rather than more, capacity is desired. One of the most significant and flexible parts of the production cost structure will be the maintenance operations scheme. As availability is reduced so is productive capacity.
The living availability design is an aggregate planning tool for exploring the ramifications of reducing productive capacity. The objective is to determine how to shift the break-even capacity utilization rate downward. In other words, to shift downward the rate the plant must run be to break even. This is done by shifting the current operational availability (A0) downward.
The operating budget cycle is the business process that gives management the image of being concerned only with the short-term perspective. However, its predecessor long-term financial vision and planning process is part of the strategic cycle (TO1).
Like long-range financial planning, the operating budget cycle is usually an annual process. However, it typically has a planning horizon of only one year. It focuses on quarterly or even monthly performance. In essence, the operating budget cycle converts the results of the aggregate plan to various budgets that are related to the owner’s short-term financial statements.
The operating budget is a synthesis of individual but related budgets. Each represents a dimension of business performance. The budgets are as follows:
The operating budget may appear short-term because the objective of the process is to study and then maximize short-term profits. However, the assumption is that the financial long-term was planned as a different management cycle.
It is also assumed, or hoped, that vital design activities, such as availability engineering, were not omitted from the plant capital project. Omission may be a result of the short-term challenge they present to traditional project tasks and management.
The long-term optimization developed by such processes greatly determines the financial results that can ultimately appear in the operating budget. For example, if the plant is not methodically designed initially to most effectively achieve the specified life cycle availability, its operating budgets will reflect the negative financial consequences. They become conditions that are at least fixed in the short-term. They may possibly even be irreversible.
Consider the consequences of availability engineering during plant design to the operating budget. The plant is designed from the beginning to be able to most profitably produce management’s specified life cycle availability. This specification was tied to a typically complex expression of financial, operating and availability performance requirements that were based on complex strategic issues.
Consequently, the period revenues would be increased as they relate to meeting availability goals implicit to the operating budget. Meanwhile, as a result of availability design, the aggregate of direct and indirect maintenance operation and depreciation expenses for the subject accounting periods will be reduced.
If availability engineering was not part of the initial and subsequent design cycles, this omission would be reflected in less attractive income and productivity of assets. Worse, not much could be done to change such an outcome in the short-term or a subsequent longer period of time.
The issue to be explored in this section is the role of availability engineering and management in the operating budget cycle. The budgeting cycle squeezes maximum short-term income from the owner’s plants as they are currently configured. Therefore, it is an iterative process with the aggregate planning (TO4) and the plant production planning (TO6) cycles.
The living availability design is a tool of those iterations with respect to determining what is possible during the operating budget horizon. As such, it is also a tool for generating realistic activity and asset-based budgets for the costs and expenses of availability management and maintenance operations.
The operating budget will also call upon the tools to optimize its system of individual budgets. The various models, especially the resource level calculation models, are utilized in this process as part of the plant maintenance operation planning cycle (TO8).
There is also a management cycle at the plant level for planning production and its resources. The objective is to convert the aggregate production plan to a shorter-term plan of production. The cycle will be short, whereas, the planning horizon may at least be a year.
The scope of the cycle is generally as follows:
Availability engineering and management is not a part of this cycle, it is an integrated, parallel cycle. It too is concerned with resource determination and acquisition. Its scope includes the planning and control of plant maintenance and support activities. Therefore, the production and maintenance planning cycles (TO8) are integrated, iterative functions. Each will empower and place constraints on the other.
The production cycle includes the preparation for production, startup, achievement of equilibrium economic production, shut-down for a host of routine and nonroutine reasons, and preparation for the next cycle. It is managed by functions and systems that control capacity, efficiency and flexibility and feed back the results to plant production planning cycles.
The availability scheme is, of course, closely tied to the production cycle just as it is to the production planning cycle. The most direct interface is the many cycles of maintenance and support that are triggered by the current production cycle. There is also the continual process of measuring and recording performance.
As mentioned, availability management through its maintenance cycle will parallel and be integrated with both the production planning (TO6) and production cycles (TO7). The elements of the living availability design will have been involved in some way with most of the previously described management cycles. Those same living design elements will also have a role as tools for supporting the maintenance cycle.
The planning and execution of the maintenance cycle must do the following:
In essence, the maintenance cycle is the act of utilizing and fine-tuning the overall plant availability scheme. The tuning serves a current range of planned production levels and scenarios. The availability engineering process will have designed the plant and its availability scheme to provide that capability. Accordingly, it will have left the systems and functions in place that will enable such flexibility to be a management possibility.
The availability model is a valuable tool for online maintenance planning. Recall that availability is not a service factor. It is a probability distribution function for expected availability performance.
The plant does not necessarily experience a shutdown or a reduced production rate when an item fails. However, it will always experience a reduction in expected availability. This is because the plant’s actual temporary configuration has become progressively different than its designed configuration.
Figure 1-3 showed that the distribution function for availability has shifted to some degree to the left. The distribution function will also take on some less attractive shape with respect to confidence limits. Furthermore, the consequence of a single failure will reflect the current status of all other plant elements as failed, ready, or functioning.
Therefore, short-term decisions in daily planning, such as the placement of a failure in queue for service work, will affect the position of the availability distribution function. In other words, with each failure, inherent availability (Ai) has been reduced. There is a lessor probability of maintaining the specified operational availability (A0). Thus, the availability model is an online tool for assessing the plant’s “instantaneous availability.” Actions should be scheduled in a response that is consistent with that condition and the desire to avoid an inevitable production reduction or shutdown.
The only true model on which a plant can be tested and evaluated as a system is the plant itself. Thus, it is crucial that management and the design engineers resist the temptation to regard the commercial production phase as only a matter of product production and its efficiency. The phase must also be respected as the testing and evaluation of a production system. Thus, it is a phase that is actually an adjunct to the research and development cycle (TO2).
Plant performance, as a production system, should be measured against the following:
The performance testing and evaluation cycle has both short- and long-term dimensions. These dimensions are in many ways a function of where the findings lead when a solution must be developed. The findings will trigger other cycles for their solution. These cycles will be a function of whether performance is to be accepted or improved upon.
Possible cycles of solution will include the following:
This may lead to a new allocation of production and resources among plants in the owner’s larger production system. It will also appear in some form as a variance in the operating budget. Subsequently, the plant’s production capacity may need to be increased by non-capital means for the planning and production periods to follow.
The product, process, and plant development cycles are presented here out of its order in the overall production system operations management cycle. It is presented at this time to better show how the other cycles will trigger them.
Periodically, there will be integrated, iterative activity or sets of subcycles to design a product, its process, and the production system to produce it. The product may be the same. Its composition or production process may be changed. Or the plant may be changed in response to changing production technology requirements such as economics, demand, and market share trends and production inputs. This, in turn, can lead to a change in the product or process.
Almost any of the other cycles can trigger this cycle. Examples are as follows:
The role of availability engineering and management in this cycle is obvious. It will use existing models for each new cycle of design, construction, and startup. However, the cycles will be using progressively better data and information as a result of the availability-centered improvement, change, and data management systems and functions.
Buffa, Elwood S. and Sarin, Rakesh K. Modern Production Operations Management. 8th ed. John Wiley & Sons. New York. 1987.
Hofer, Charles W. and Schendel, Dan. Strategy Formulation: Analytical Concepts. West Publishing Company. St. Paul, Minn. 1978.
Katz, Daniel and Kahn, Robert, L. The Social Psychology of Organizations. 2nd Edition. John Wiley & Sons. New York. 1978.
Tersine, Richard J. Production Operations Management Concepts. 2nd ed. Prentice Hall. Englewood Cliffs, N.J. 1984.
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