Proceedings of the2011 Industrial Engineering Rearch Conference
T. Doolen and E. Van Aken, eds.
Ast Management: A Systems Perspective Vhance V. Valencia, John M. Colombi, Alfred E. Thal, Jr., and William E. Sitzabee
Air Force Institute of Technology
Wright-Patterson Air Force Ba, OH 45433
Abstract
From a facilities and infrastructure perspective, ast management is often viewed as a framework to facilitate more informed decision-making by combining engineering and business principles. The Federal Highway Administration defines it as a performance-bad framework to efficiently manage built facilities from a life-cycle perspective.As such, it reprents a systematic process for maintaining, upgrading, and operating physical asts in a cost-effective manner with a focus on potential interactions within the universal system and its components. Viewed in this manner, it would em that systems engineering principles would have broad applicability to the field of ast management. Theref
ore, the purpo of this paper is to provide a comparative analysis of systems engineering and infrastructure management best practices. Specifically, we explore synergies between the two fields and hypothesize that the ISO 15288 process can be applied to the engineering management of the infrastructure. After defining infrastructure and ast management, we show how systems engineering tools, techniques, and methodologies can be ud within the context of broad infrastructure ctors and critically analyze the connections between infrastructure management and systems engineering. In general, we show that systems engineering principles have broad applicability to ast management but are not widely ud.
Keywords
Infrastructure, ast management, infrastructure ast management, systems engineering
1. Introduction
In 1998, the American Society of Civil Engineers relead its first “Report Card for America’s Infrastructure” in which it awarded an overall grade of “D”for the national infrastructure. Since then,it has issued subquent report cards in an attempt to highlight the impending failure of the nation’s infrastructure and elevate infrastructure needs on the U.S. national agenda [1].However, infrastructur
e systems are complex, vast, and thus difficult to manage. Therefore, applying a systems approach to the management of civil infrastructure is gaining acceptance within the infrastructure ast management field [1-3],but application of systems methods, process, and techniques is limited and varies according to infrastructure ctor. With this paper, our goal is to provide a comparative analysis of systems engineering (SE) and ast management(AM)best practices from the past 10 years. Specifically, we aim to show that the International Standards Organization (ISO)15288 process, as described in the 2010 INCOSE Systems Engineering Handbook (v 3.2)[4], can be applied to the engineering management of infrastructure.
2. Infrastructure Ast Management
There are many ways to define infrastructure ast management. For example, the U.S. Department of Transportation defines ast management as a systematic process for maintaining and operating physical asts cost-effectively through a combination of engineering principles and sound business practices[5]. Similarly, the Transportation Ast Management Guide [6]considers the core elements of ast management to center on the process of resource allocation to effectively manage asts. The elements of this process consider the following tenets: an approach that is policy driven,options and trade-offs analys,effective rvice and project delivery, decision-making bad on quality infor
英语学习网站有哪些vacantmation,and continuous monitoring of the information ba for feedback into updates and improvements. Hoskins, Brint, and Strbac[7]describe ast management as activities for the upkeep of a given infrastructure system such as inspection, maintenance, repair, and replacement of parts of the system network all at minimum cost. Finally, Grigg[8]synthesizes an ast management definition as “an information-bad process ud for life-cycle facility management across organizations.” He goes on to write that important features of the definition include an “asts” view of the infrastructure system and its component, life-cycle management, enterpri-wide u of ast management, and the u of information-bad process and tools.
The common themes among the varying definitions lead us to offer our own definition: “Ast management is the holistic asssment of a given infrastructure system using a life-cycle approach bad on quality data for the purpo of optimally managing physical asts at least cost to stakeholders.” This definition recognizes veral themes. First, there is a growing acknowledgement within the infrastructure industry that a holistic, life-cycle view, or systems view, can provide the tools and techniques needed to address infrastructure issues. Second, it recognizes the purpo of ast management can only be realized with quality data about the infrastructure system. Finally, the definition identifies that ast managers have a duty to minimize cost to stakeholders. The costs above the moon
are not only fiscal constraints on operating budgets, but should be inclusive of the entire life-cycle cost of the system and intangible costs such as environmental health, loss of public trust, and other social costs.
3. Systems Engineering
Similar to ast management, many authors have provided varying definition of systems engineering [9]. However, the International Council on Systems Engineering (INCOSE) has published a handbook that offers a description from the synthesis of three definitions[4]:
Systems engineering is a discipline that concentrates on the design and application of the whole (system) as distinct from the parts. It involves looking at a problem in its entirety, taking into account all the facets and all the variables and relating the social to the technical aspect[10].
Systems engineering is an iterative process of top‐down synthesis, development, and operation of a real‐world system that satisfies, in a near optimal manner, the full range of requirements for the system[11].
Systems engineering is an interdisciplinary approach and means to enable the realization of successful systems.
It focus on defining customer needs and required functionality early in the development cycle,documenting requirements, and then proceeding with design synthesis and system validation while considering the complete problem: operations, cost and schedule, performance, training and support, test, manufacturing, and disposal.
SE considers both the business and the technical needs of all customers with the goal of providing a quality product that meets the ur needs[12].
When considering common themes of systems engineering from the handbook and other works, it is clear that ast management and systems engineering share many of the same core concepts. For example, a life cycle approach taking a holistic view is central to both SE and AM. Recognition that stakeholders determine value of the outputs of the system is another shared theme between the two fields. Optimal design, operation, and management of a system through informed decision-making are also goals shared by both fields.
4. The Need for a Systems Perspective
Many rearchers and practitioners contend that traditional infrastructure management approaches are no longer effective. Godau [2, 13]makes this claim due to complexities from technology and oth
er external factors such as economics, politics, and the environment. Robinson, Woodard, and Varnado [14]echo the need for change as infrastructure systems are now more interconnected than ever. The American Society of Civil Engineers, through in-depth roundtable discussions, found that a common thought among discussion participants was the need to take a systems approach towards the nation’s infrastructure[1]. The underlying premi held by the rearchers and practitioners is that a systems orientation will help solve problems encountered in the management of infrastructure. Indeed, some within the SE field feel that the profession can rve as a framework for engaging in this problem. Cook and Ferris [15]write that SE, as a multi-methodology, is an appropriate way to solve traditionally non-SE problems provided that the solution will be technical in nature. INCOSE itlf has developed an Infrastructure Systems Working Group (ISEWG) who membership concerns itlf with the application of the discipline of SE to physical infrastructure. The ISEWG published a special infrastructure issue with its editor stating[16]:“individual infrastructures,as well as the collective infrastructure,obey all the rules of systems. They are all collections of asts, the subsystems, which individually and collectively perform functions ... they can be considered a system of systems (SoS) since they interact with each other.”
The special issue goes on to highlight the SE applications to infrastructure such as rails [17], highwa
ys [18], water [19],and energy [20]. All contributing authors to this issue conclude that SE undoubtedly has applications to infrastructure ast management.obl
The application of SE provides benefits to the field of ast management. One such benefit is the understanding of system interfaces as the definition and management of the interfaces is central to SE–it is the interactions of the parts that produce the results desired out of the system [21]. At the design stage, a systems approach will generate a greater understanding of not just the desired end-product, but also the problem at hand potentially leading to a superior system. Finally, during operations and maintenance, infrastructure managers taking a systems view and holistic decision-making approach might e reduced failures, reduced system risk, optimized functionality, and optimized maintenance cost –which are benefits addresd in the papers reviewed for this study.
5. Comparative Analysis of SE Process and Ast Management Practices
As previously stated, not all SE tools, techniques, and procedures are directly applicable to the field of ast management. In fact, Godau [13]suggests that SE should be tailored to match infrastructure specific problems. With this in mind,of the 25systems engineering process and life-cycle stages specified by ISO 15288:2008, we highlight six of the process and demonstrate thei
r applicability to the needs of infrastructure managers. The remainder of the paper relates the six SE process to ast management practices and rearch found in the literature. As a starting point, the International Infrastructure Management Manual (IIMM) [22]is referenced against the process descriptions outlined in the INCOSE Handbook (v3.2) [4]. Practices and applications in the literature are ud to illustrate the SE process concepts in u. Figure 1 illustrates the direct comparisons of the SE process to be investigated to broad process of ast management.
Systems Engineering Infrastructure Ast Management Stakeholder Requirements Definition Process Levels of Service Decision Management Process Optimized Decision Making
Risk Management Process Risk Asssment and Management Information Management Process Information Systems and Data Management Measurement Process Measure Levels of Service Life CycleManagement Process Life Cycle Ast Management
Figure 1. Comparison of six SE process to six AM process.
5.1 Stakeholder Requirements Definition Process
The first steps in establishing ast management process are similar to the first steps in systems
engineering. In SE, the initial pha of any given product is to determine stakeholder requirements which in turn drive system development. For ast managers, given that infrastructure systems are already in place,and once ast inventories have been established, their objective in defining stakeholder requirements centers on establishing levels of rvice [22]. This process involves gmenting the customer ba into identifiable groups and then understanding what the customers value. This is necessary becau, just as in SE, the differing values, agendas,needs, and interests of the various stakeholders are ud to judge the efficacy of the organization. For SE, organizational efficacy is measured against the final product delivered; for AM, this is judged by the level of rvice provided.
The question of how to determine the appropriate level of rvice is a topic addresd by a number of rearchers. Rogers and Louis [23]and Ramesh and Narayanasamy [24]explore this question with regards to water rvice. The former studied community water systems in the U.S. and the latter rural water delivery in India. Both found that system inefficiencies resulted from decision-makers failing to properly account for stakeholder requirements. Specifically, Rogers and Louis [22] contend that typical decision approaches lead to short-term positive impacts for the immediate community (i.e.,incread economic activity through capital improvements) but potentially result in n
egative long-term impacts (i.e., system deterioration becau of deferred maintenance). Ramesh and Naraynasamy [23] find that in failing to recognize the lack of technical capability for municipalities in operating and maintaining water infrastructure,the Indian government has provided excessive infrastructure which has resulted in excessive water waste across the country. Rogers and Louis [22] offer that a systems analys approach could help in bringing appropriate levels of rvice from community water systems.
Work in the transportation ctor concerning levels of rvice also begins with asssing stakeholder requirements. Yin, Lawphongpanich, and Lou [25]provide an approach that estimates the necessary investment for maintenance and repair of highway networks to maintain or increa levels of rvice. Their mathematical model accounts for ur preferences when deciding routes and factors in unknowns such as travel demand and ast deterioration. They report that their model prents solutions that provide equivalent levels of rvice as compared to conrvative investment plans but at a much lower investment cost. Similarly, Yang, Bell, and Meng [26]prent a model that determines appropriate road capacity and levels of rvice by also accounting for route choice behavior of travelers.
5.2 Decision Management Process
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Another key process for AM and SE practitioners is the decision management process. The definitions in the two fields are similar in that the process involves lecting the optimal decision among a number of alternatives. Other similarities in this process include utilization of classical decision-making approaches, namely risk-bad and multi-criteria decision-making, and the u and development of decision-making models.
Both fields recognize that there are two broad types of decision-making approaches: risk-bad decision-making and multi-criteria decision-making [9, 22]. The risk-bad approach quantifies the alternatives and, combined with the likelihood of an outcome, leads to the basis of a decision. Even though the IIMM emphasizes cost as the primary means for quantifying alternatives, other ast management studies u different methods for quantification. For example, Seyedshohadaie, Damnjanovic, and Butenko [27]u the idea of risk as a basis for maintenance approaches on transportation infrastructure. Ast management has wide-ranging stakeholders with varied agendas and so intangible impacts are significant to ast managers. The multi-criteria decision method ems to be able to address intangible impacts and there are a number of works that prent multi-criteria decision methods in transportation [28, 29], facility management [30],waste management [31, 32],and energy [33].
Given the decision-making approaches, decision-making models are a necessary component to the process. Blanchard and Fabrycky [9]suggest that decision-making models and simulations are uful tools in the process as they enable the study of the system at far less cost and with far less time compared to direct obrvation of the system. The u of decision models are widely ud in ast management. Fenner [34]reviews decision methodologies in the water/wastewater ctor and finds that current models lead to maintenance activities only on the highest risk or most critical wers. He suggests a change in established decision methods is needed so that maintenance activities are carried out that affect the wider catchment system. He also reviews promising developments in his field such as non-critical wer asssment, wer survival models, usage of performance indicators, risk analysis through diment build-up, and rehabilitation cost analysis, but finds that a lack of data prevents meaningful analysis of options by municipalities. Similar to Fenner, Hoskins et al. [7]suggests that changes to electricity industry decision models are necessary and prents a decision approach that recognizes the constraints of limited budgets. Claiming to be generalizable to other infrastructures, their six-step approach is contingent on the ability of managers to quantify and model the condition of a component, relate the component to the overall system, and then model the component’s deterioration over time. This approach promis to lead ast managers to more informed decisions;however, much like Fenner, Hoskins et al. [7] finds that the availability of data limits the quality of decisions.
5.3 Risk Management Process
There is considerable overlap in how ast management and systems engineering treat risk management. Both the SE Handbook and IIMM provide similar outlines for the risk management process with key steps including tting the risk context, identifying the candidate risk, analyzing each risk, developing risk treatment strategies, and continuous monitoring and review of the risk management process [4, 22]. Additionally, both sources define risk in the same manner and that risk is compod of the likelihood an event will happen and the conquence of that event happening. Finally, both advocate the u of risk rating tables to visually depict the magnitude of a given risk. Although the considerable overlap suggests that risk management is a well-developed concept in SE and AM, veral studies offer insights that may allow even greater incorporation of risk management into the ast management process. For example, Piyatrapooni, Kumar, and Setunge [35]suggests the u of risk maps that synthesize individual risks onto a single graph and categorize each risk event into one of three “tolerability regions.” Risk mapping could then be incorporated into the decision-making process to lead to more confident decisions by ast managers. Austin and Samadzaeh[36]propo a novel metric for systems engineers to measure the effectiveness of a risk management system. They found that a large body of literature exists which evaluate
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different risk management systems, but found that the literature did not offer a “risk management effectiveness”metric. They propo a measure of effectiveness metric with the aim to contribute to the improvement of the overall SE risk management system. This metric is fully applicable to ast management systems. Specific applications of risk management principles in differing ctors of infrastructure include applications in facility management [37], water infrastructure [23, 38], transportation[27, 39], and energy [40, 41].
oldboy5.4 Information Management
The SE information management process is the overall process that ensures relevant information is collected, available in a timely manner, valid and complete, and accessible through an archive databa of information [9]. Ast managers recognize the need for information management systems[5, 42-44]. The IIMM provides characteristics of good ast management systems which include proper information architecture, ea of upgrades and expansion, ability to integrate data across platforms, adequacy of information technology support, and sufficient resources provided by the organization to support the information management system[22].仁和会计
Examples of information systems ud by ast managers are geographic information systems (GIS)
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which relate geospatial data to specific components of an infrastructure system,maintenance management systems (MMS) which store and manage information regarding an organization’s maintenance activities,and pavement management systems(PMS)and bridge management systems(BMS) which are ud extensively in the management of U.S. roads and bridges. The and other tools like them enable the collection and analysis of ast data and are central to effective ast management process [5]. In addition to data collection and analysis, other key components of the systems include feedback and update mechanisms, analytical models, and built-in process which identify and recommend capital improvement, maintenance, and repair investment strategies. The u of information management systems has been proven to increa management effectiveness [5, 45];however,the increasingly complex, interdependent nature, and data availability on today’s infrastructure systems prent a data management problem in the form of data integration for ast managers.
Much like SE, information system data integration is of importance to ast managers becau poor integration results in organizational inefficiencies and suboptimal decision-making [42, 43]. Problems of current information process include: (1) data storage within “silos” resulting in duplication and inconsistencies,(2) data errors resulting from translation and re-entry into different sy
stems,(3) data source fragmentation which creates difficulties in generating comprehensive views,and (4) an overall, highly inefficient information management system[42, 43]. Data integration is not a new field of study in AM as the past two decades include works addressing this problem [42, 46]. However, the works report that ast managers are behind other fields in addressing this problem due to organizational fragmentation across industry and government. Organizational fragmentation leads to data fragmentation and prents a rious challenge in data integration. Given information’s central role in ast management, it is imperative that data integration be taken into account when developing AM information systems.
5.5 Measurement Process
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Tied to the information management process is the measurement process. The measurement process as defined by INCOSE is the collection, analysis, and reporting of data on product performance and organizational process which support management decision-making and contribute towards performance improvement of the system[4]. Similarly, ast managers collect performance measures for the comparison of system performance to levels of rvice. The IIMM categorizes the measures into two types: ast condition states and system performance[22]. Two particular concerns are the ability for ast managers to provide accurate measures of condition
states and the ability to determine future performance of infrastructure systems.
Ast condition states and system performance do not necessarily have direct relationships with each other[22]. A degraded ast may or may not lead to degraded system performance and degraded system performance is not necessarily indicative of degraded asts. For example, water pipes with vere corrosion could still function properly in transporting water. Alternatively, a poorly functioning electrical grid does not necessarily point to inefficiencies from degraded substations, electrical lines, transformers, or other asts. Such cas could be caud from operator error or vere weather. However, a failed condition state of an ast would undoubtedly lead to performance failure. So although the metric of interest is system performance, ast condition states must also be measured to prevent system performance failure. Of interest in the literature is the u of remote nsors for structural health monitoring of civil structures such as bridges and buildings [47-49]. The rearchers explore recent developments in the design and u of nsor technology given its low cost and accessibility as compared to
