ABSTRACT
Most enterprise asset management (EAM) systems do not address the complex demands of managing linear assets such as railroads or pipelines. The key requirements needed in such systems, for linear asset management (LAM) that is both technically and financially effective, are discussed and described.
INTRODUCTION
‘A place for everything and everything in its place’
is the key to pristine linear asset data.
Organisations managing linear or continuous assets such as roads, rails, pipelines, and electrical transmission lines face unique asset management challenges, yet don’t have fit-for-purpose tools to manage them optimally. Most enterprise asset management (EAM) systems do not address the complex demands of linear asset management (LAM). Typically, EAM solutions are purpose built for corporate ‘enterprise’finance and resource planning stakeholders, and often don’t take into account the demands of managing field-based assets that are not in a typical hierarchical arrangement – these would be linear assets.
The result has been a reliance on disparate systems and processes to store and report on performance and cost data, schedule and prioritize work, and track work progress for linear assets. Linear asset owners that have integrated engineering tools during enterprise system upgrade programmes in recent years, are having to find workarounds for linear asset referencing in their asset management departments.
While this may seem minor, the performance of these assets is the life-blood of these businesses. In many cases, the resulting losses could not be recaptured if they were to fail – such as lost revenue and lost customer satisfaction from energy outages, customer impacts caused by delays in getting goods to market via freight rail, or regulatory fines from mismanagement of public infrastructure assets.
Linear asset owners must optimize the value and performance of every asset throughout its lifecycle, while maintaining the highest levels of safety, quality, performance, reliability, and regulatory compliance across their infrastructure.
“A place for everything and everything in its place” is the key to how linear asset data and information is appropriately defined in your asset management system – having the right information at the right time determines how effectively you can manage it.
Having high performance quality linear asset information requires a keen and sharp focus on linear asset master data governance – a process to keep data perfect. Providing linear asset stakeholders with trusted asset information requires your EAM solution to have the flexibility to deal with a variety of data definitions, as well as controls to ensure the linear asset information is pristine and relevant.
This paper describes five key requirements that linear asset managers need in an EAM system and how these can impact the bottom line:
- Flexibility and control to define linear assets dynamically
- Managing assets out in the field
- Getting a clear financial picture
- Implementing the right asset management strategies
- Anticipating the future of financially optimized linear asset management
FLEXIBILITY AND CONTROL TO DEFINE LINEAR ASSETS DYNAMICALLY
Organisations often need to report on linear assets in different ways. For example, railways need to be able to accurately define location attributes along a track section for the purposes of work assignment, scheduling or cost management. Similarly, when integrating with expert systems such as video camera rail inspection tools, rail head condition data for a specific section of rail must be in sync with the equipment register so that operations and engineering people can leverage the EAM system to make definitive decisions on the severity, risk, criticality and duration of an outage to correct adverse rail conditions.
Another requirement is the ability to define a continuous asset within your network, such as a highway or rail line, not only as a discrete entity but also in terms of both physical and financial context. For example, whereas the physical characteristics for a given line of track are fixed (metres or miles) in nature, the operation context may be defined in multiple segments with varying operating (speed) and financial (cost) definitions.
From the perspective of the asset register, these operating and finance attributes may change during the expected asset lifecycle of the track, based on maintenance strategies applied. These capabilities are essential for optimizing your field operations, and to facilitate costing, financial analysis and reporting in line with your business requirements. If linear assets can only be defined in terms of fixed divisions (e.g., a set length or physical distance), you will likely face complicated, manual analyses and reporting to work around this lack of flexibility.
With respect to railroads, positive train control and operation requires a wide spectrum view of linear assets plus weather, traffic volume, and track speed limits. Triangulating all this data in near real-time has a significant impact on tracking of maintenance strategies, asset condition, and lifecycle costs.
For maintenance costing, financial analysis and other reporting purposes you might wish to define railroad segments of shorter or longer lengths – or even varying lengths – along the asset network. A highway might be defined as a single asset spanning from mile marker 1 to a district boundary at mile marker 210. You might further wish to manage work and costs by defining mile-long segments within a short radius of population centres due to their higher traffic volumes. In outlying areas the asset could be subdivided into five-mile segments. You could similarly segment the highway relative to surface type, service level needs and/or other considerations.
Organisations also need to have”everything in its place” to track the relationships between linear assets and the discrete assets and other features associated with them. Therefore it should be possible to track these items both in a GIS context and within the EAM system using linear features attribution.
Having a solid master data governance (MDG) program and solutions to rationalize and normalize linear master data is critical to linear data health.
Examples of linear asset feature data include not only signals, track sensors and switch gear but also characteristic data that provides decision support information such as speed restrictions in specific areas, the precise locations of natural features alongside a railroad track, easements on land below grade, and so on.
MANAGING ASSETS OUT IN THE FIELD
Most linear assets are geographically dispersed, so maintaining them requires a mobile workforce with the ability to pinpoint exact locations along assets for inspection, maintenance and defect reporting purposes. When referring to specific locations of assets and work, it is often useful to be able to shift automatically between physical and geospatial references as appropriate. For example, in a public transit operation when a complaint is made about a dirty or damaged bus shelter, the operations team would reference the transit planning system to accurately pinpoint the location along the bus route to create a work request in the EAM system. A work order would be produced with accurate work location, asset configuration data for the shelter, and spare parts needed to execute corrective action. The geo-reference coordinate for that bus stop would be used by the maintenance planner to determine the nearest, most available work crew. The planner would insert this activity into the work crew’s route and push the order to the crew’s mobile work order device. Once the work order is completed this record would be used to generate frequency and severity data used to produce work pattern and asset reliability reports by location, to improve maintenance strategies or equipment specifications.
The concept of “a place for everything and everything in its place” is once again critical to acquiring field based data points from “expert” design/planning systems and asset health tools like rail track symmetry and road pavement inspection systems. The ability to refer between physical and coordinate location references is essential to supporting the asset lifecycle through integration with GIS. It directly enhances operational and field functions like surveys, inspections, maintenance, repairs and new construction. Precise location data makes it easier for crews to navigate to the right spot so they can more efficiently record inspections and defects, and perform maintenance and repairs. This makes it easier for dispatchers to “see” where the work is, and adjust scheduling and dispatch accordingly. The benefit is that the entire field workforce can be more efficient by correlating the locations of multiple work items in an area. This enables crews to do more work with fewer resources – saving travel time, reducing the need to dispatch multiple crews, and helping to ensure crews have all the information and equipment they need to complete their work orders. It’s all about having the right people, with the right parts, in the right places.
Once the crew is at the right location, managing the asset in the field effectively requires the ability to perform work safely and within the asset management policies. Enabling the field with the right mobile tools can dramatically improve productivity and safety. Such tools should provide access to full asset history, the ability to visually identify parts, step-by-step instructions for work and safety checklists, and simple tools to actively update and log jobs from out in the field. Back in the head office, dispatcher dashboards will display exact coordinates of their teams and the status of their work – improving scheduling capabilities and allowing management of operational and environmental risks.
Based on the savings in crew windshield drive time alone, some transportation companies could improve productivity by over $30 million a year – not to mention improvements in inventory handling, field safety and work quality.
Unfortunately, many companies trying to deploy generic mobile service applications against their ERP are not achieving anywhere near that level of productivity improvement. Linear asset managers need to take control to get the requirements they need addressed by deploying a tightly integrated linear asset management (LAM) and mobile work solution.
GETTING A CLEAR FINANCIAL PICTURE
Companies with significant portfolios of linear assets can face unique challenges when trying to maintain a clear financial picture. For example, it is often difficult to get the views you need, such as when you need to break costs down to the specific segment, roll costs up to support your district structures, and manage capital projects effectively.
Recording maintenance costs accurately
When performing work on any asset, you need the ability to track the work and associated costs in a variety of meaningful ways. Otherwise it becomes difficult to identify areas where costs are higher or lower, and then to implement strategies to address this. For example, if a crew performs cathodic inspection on a valve somewhere on a gas pipeline network, you need to be able to track the cost of that work against the proper segment of the asset. At the same time, you need the ability to roll up valve-related costs across all the segments of the asset, so you can compare maintenance costs in different areas. As described in the example just given, work orders can be used to plan, schedule and execute work on linear based assets.
A best-in-class LAM system would leverage work orders as an instrument capable of tracking any relevant work activity from both operational and financial perspectives. In this context, expense elements like labour and parts, along with other operational and financial details, should be retained with the asset record – readily available to support a wide range of analytics and decision support.
Support for managing “districts”
Transportation departments, government agencies, utilities and other organizations that maintain linear assets over large geographic areas often wish to manage them in terms of “districts” or similar geopolitical regions. Associating assets with specific “districts” or “regions” can support operational autonomy and flexibility in line with organizational structure. In this way, districts can more easily maintain their own budgets for their overall operations or for individual projects. Of course, “district” level cost and performance data need to roll up through the organizational hierarchy to support reporting, strategic planning and investment analysis. What is required at the LAM level is the ability to logically segment the enterprise in whatever way optimizes operational efficiency, financial reporting and budgeting activities.
While only one instance of a linear asset, such as a highway or transmission line, would exist within the EAM system, the asset might traverse multiple “districts” and be managed in part by each of them. It should be straightforward to realign boundaries and assets to support operational needs without impacting work history, lifecycle costs and other asset data – a critical need given the changing dynamics of customers, budgets, organizational structure, etc. A best-in-class EAM system would leverage work orders as an instrument capable of tracking any relevant work activity from both operational and financial perspectives.
Managing capital projects efficiently
Linear asset intensive organisations frequently need to identify multiple levels of activity (project, sub-project, work order, etc.) as capital projects, in whole or in part. The LAM system should therefore make it easy for you to apply maintenance, repair, construction and/or project costs to specific segments of a linear asset, or across multiple segments or the whole asset. You should be able to straightforwardly create projects of arbitrary complexity, and modify them over the course of construction activities. This makes it much easier to manage activities and costs at the capital project level, while appropriately associating costs with asset segments for other costing and maintenance purposes.
IMPLEMENTING THE RIGHT ASSET MANAGEMENT STRATEGIES
Because linear assets are widely dispersed, their characteristics and condition tend to vary along their length due to uncontrollable environmental factors. Linear assets also invariably encompass numerous discrete assets. What sections of an asset need more or less maintenance or repair? How often does an asset segment need to be inspected or repaired? What is the annual maintenance cost of one specific segment of an asset versus another, and why do they differ? Answering these kinds of questions reliably helps optimize asset maintenance. But simply streamlining preventive maintenance programmes will not generally drive significant gains in asset availability, maintenance costs or labour utilization. A more proactive, health-based approach to maintenance, such as condition monitoring and predictive or reliability-centred maintenance, is required.
Support for linear asset predictive maintenance
Predictive maintenance focuses on leveraging experiential data to gauge the condition of assets. This maintenance strategy seeks to predict when maintenance should be proactively performed. This approach is efficient and “smart” and saves both maintenance and repair costs over routine preventive maintenance, by allowing tasks to be performed when actually required (as opposed to too frequently or not frequently enough). A regular inspections programme is the key to any predictive maintenance programme. But due to their geographically dispersed nature, it can be difficult to inspect linear assets easily or often enough to support adequate monitoring. Predictive maintenance strategies can leverage holistic LAM data across history, mobile inspections, and manufacturer specifications to help you inspect more efficiently.
Linear specific maintenance instruments
Maintenance plans should contain linear reference data like patterns and offsets, and these need to be aligned with geospatial coordinates – maintenance plans prescribe the ‘why and when’; the linear asset information identifies the ‘what’ and the geospatial location data the ‘where’. Accurate asset and location information is the foundation for effective dispatch and asset programme planning and scheduling.
Asset management based on condition monitoring
Going a step beyond periodic inspections, extending asset life and improving reliability can be accomplished through condition based monitoring that tracks one or more key condition parameters for a linear asset, such that a change defined as significant can indicate a greater possibility of failure. This raises an alert, and drives maintenance or other actions (e.g., creation of work order or inspection jobs) to be scheduled automatically to prevent a failure. Some examples include track inspection rail cars equipped with automated track recording as well as ultrasonic rail flaw detection systems.
Sustaining linear data quality with master data governance
Once the linear asset with geospatial master data (locations, maintenance plans, tasks etc.) are in alignment with asset maintenance strategies, data stewards need to keep dynamic linear attribution in sync with static geospatial coordinates. Implementing a solid IT/OT information management of change (MOC) programme that keeps linear data clean and dependable is key to ensuring repeatable success.
ANTICIPATING THE FUTURE OF FINANCIALLY OPTIMISED LINEAR ASSET MANAGEMENT
Better condition based monitoring is the foundation for analyzing asset health and performance to identify underperforming areas and allocate capital improvement resources. For example, a segment of overhead wires that is performing poorly due to exposure to environmental conditions may be a candidate for a capital improvement project to improve its overall condition, as well as an indication of the need to modify maintenance strategies to reduce future costs. Greater convergence, visibility and “intelligence” between operational technology and information technology systems have the potential to bring more and more real-time asset health and performance information into LAM solutions.
A better-informed response to real-time asset health can revolutionize linear asset management, enabling unprecedented agility in response to changing conditions. In particular, the convergence of IT and OT can make more real-time data on asset state and health available to streamline maintenance effectiveness. Integration of condition monitoring, inspection data and work processes can drive a dynamic, highly automated reliability centred maintenance (RCM) strategy. For example, a combination of asset history combined with condition data that indicates a potential risk could automatically trigger an inspection order for the nearest crew.
In the case of a defective positive train control component, with trusted linear asset data the dispatcher can quickly pinpoint the failure and the environment condition in the area from weather feeds. With all this information, the dispatcher can accurately determine the impacts on customers, gauge the scope and risk of the situation and dispatch work crews. In many cases these can be life-saving decisions.
A further benefit of IT/OT integration is that over time asset historical data becomes increasingly rich, enabling organizations to better understand the true condition and health of its assets. The direct linkage of asset condition monitoring data with inspection/work data stored in the LAM system helps build stronger business cases for repair versus ongoing maintenance of an asset segment, for instance. The organizational and financial benefits of an asset health centred strategy are enormous: it can enable operations to better support the organization, while freeing up capital to focus on improving and creating new networks that can successfully service the demands of customers not just now, but in the future.
SUMMARY: GETTING ON THE RIGHT TRACK FOR MANAGING LINEAR ASSETS
Linear asset management demands “a place for everything and everything in its place” for defining assets, specifying location data, analyzing costs and streamlining maintenance for optimal network performance. The LAM system needs to address these requirements to optimize asset performance, availability and safety.
A quick checklist of the major capabilities required for managing linear assets includes –
- Flexible definitions of segments supporting different work and financial requirements
- The ability to track relationships between linear and discreet non-linear assets
- Precise location data with alignment between geospatial coordinates and linear reference points
- Tight integration between LAM and GIS and master data governance to sustain data integrity
- Industry-specific mobile work tools built to tightly integrate to your LAM system
- Mobile work solutions that –
- Tightly link to your EAM to pull asset history
- Allow you to identify correct parts in the field visually
- Support step-by-step field crew processes built for your industry
- Align field work to your asset management policies
- Provide safety checklists and industry-specific compliance functionality
- The ability to report on costs accurately:
- By linear segments / patterns
- By district
- Seamlessly between capital work and operational management
- Integration with industry-specific condition monitoring solutions
- Templates leveraging best practices for equipment maintenance
- Support for advanced predictive maintenance
- Integration to asset health intelligence and dashboards
- Support for integrating IT with OT
- Focus on master data governance (MDG) policies, practices and tools
By having a fit-for-purpose LAM solution for managing linear assets, organizations can reduce maintenance costs and overall operating costs, thus freeing up funds for capital improvements. More efficient and effective maintenance tactics enabled at the linear asset level will drive optimal asset reliability resulting in better customer service levels in relation to cost. These benefits will yield increase revenues, improved return on assets and greater customer satisfaction.
About the author
Jim Charboneau is Director, Rail and Utility Solutions for Utopia Inc. with a global focus on data services and enterprise master data governance solutions for asset intensive industries like oil and gas, power generation, mining and rail transportation.
From his roots as an apprentice trained maintenance professional on the railways of Canada Jim has risen to more recently lead Enterprise Asset Management consulting services practices for Price Waterhouse Coopers Canada (PwC) and global engineered products firm ASEA Brown Boveri.
In his role at Utopia, he provides the industrial computing space with thought leadership and trusted advice on the topic of master data governance, data visualization and analytics. He is well known as a social media lion on LinkedIn where he moderates 25 Groups on the topic of EAM / Enterprise Asset Management.
Utopia is a global software, consulting, and services company specializing in enterprise data solutions that enable management and governance of critical master data for an enterprise. Its “build, fix, and sustain” approach, along with best-in-class software, empowers our customers to get their data right, and keep it right.