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Data-driven diagnostics

Enhancing mature asset operations and improving process safety through good data maintenance and management.

Mark Cowan Service Line Lead

by Mark Cowan

Managing Consultant, Safety & Risk

25 August 2017
Data-driven Diagnostics

With tight markets and high-operating costs, asset-intensive organizations need cost-effective ways to maintain the production, integrity and safety of their assets.

 In many cases this process has been inefficient and inconsistent, and at times, offered incorrect results. As we move into the era of data-driven solutions, there are a number of opportunities for asset-intensive organizations. They can take advantage of available technologies to help them use their data more efficiently, extending the life of their assets and ensuring productivity, safety and performance step changes.

The information is there, but could it be managed better?

As an asset evolves, so too does the data and information that surrounds it. Iteration after iteration of prospective plans, updates from maintenance checks, real-time data analytics and other records all make up what is often called the "digital asset." This digital asset can tell a profound story about a physical asset’s current condition. 

The challenge for asset operators is to manage this information efficiently and ensure it is used at the right time to support organizational decision-making frameworks. This is particularly important when it comes to using operational data effectively to assess the integrity, safety and performance of an asset during daily operations. 

Quite often asset information is siloed, housed in a poor management system. As a result, it isn’t utilized properly or kept up-to-date. In an ideal world, asset-intensive companies would track the information for all components that make up an asset in a single, end-to-end process that informs operations, maintenance and integrity.  

But we already know this. We know that creating a digitized data model of an asset will improve safety risk, maintenance activities, procurement and overall performance. These models are being developed by a number of companies across industries where financial, human, physical and data information frameworks work in collaboration with tools, authorities and accountabilities as part of an integrated asset management structure. 

What’s missing are ways to transfer these models into a mature operations environment where the normalization of cultures and systems often prevent the development of enhanced asset integrity and safety management. 

Shifting the way we approach the project from the very start

Building and operating assets generates immense amounts of data. A systematic view of how data will be captured and used for subsequent governance processes needs to be developed based on a one team, one objective model.

A mature asset management strategy must be determined through a well-documented and embedded approach to using available data as a single source of truth. Without this approach, we could be lowering our defenses against major events such as Texas City and Buncefield. 

Such events have intensified focus on process safety integrity, leadership, key performance measures and organizational competence in recent years. However, the UK’s Health and Safety Executive (HSE), among others, is still seeing evidence of process safety management practices and accountabilities being disjointed, with a wide variety of interpretation of their implementation. 

What’s more, the latest EU Major Accident Hazard (MAH) directive, "Seveso III 2015," calls for operators to review past accidents and incidents with the same substances and processes used and ensure the lessons learned and findings are integrated into their operations. 

Key to this is the removal of the "silo factor" and the development of a clear information management framework covering each asset and the organization as a whole. 

Three key steps

To support the implementation of an integrated framework for mature assets, three key steps are typically required:

Three Key Steps

1. Assuring strategic implementation across all stakeholders

A structured and coherent Operational Data Management  strategic policy must be built. This strategy needs to incorporate all the correct systems – current and new – that will set the business and asset up for future success.  

Typically, each constituent member of the organization has a recognized role to play in delivering the organization’s operating integrity performance. Effective implementation can only be achieved through a fully integrated and collaborative process that encourages a constant team "uneasiness" regarding the potential impacts of major hazards and how their latent conditions evolve through an inefficiency to manage performance related data.  

2. Data capture and remediation

If you’re capturing your data incorrectly or inefficiently it could cost you millions – in data remediation or as a result of poor operations maintenance planning. Data capture is continually becoming smarter and cheaper and there are an abundance of technologies available to help organizations manage this process. To ensure these technologies are embedded properly into the organization, a shift in the way our people think about data capture and its importance is needed to see a lasting change, and to ultimately reap the benefits. Defined data stewards trained and responsible for data information decision making should be embedded across all functions, but managed at a corporate-wide level. 

3. Using data to facilitate a mature asset change

Mechanisms are required to maximize the use and reuse of information. Our organizational resources need to be aligned to work in a new manner. To facilitate change, clear lines of data accountability, communication and integration across business teams and project phases will need to be developed.

Disparate information sources abound – Process Flow Diagrams (PFDs) & Piping and Instrumentation Diagrams (P&IDs), models and drawings, data sheets, vendor data, geographic information system (GIS) data, operating procedures, design documents, class library data and regulatory submissions to mention a few.

Without an embedded asset data strategy, your asset integrity will suffer

Enhanced process safety through effective operations data integrity requires an integrated approach across the organization. With siloed behaviors increasing, the risk of holes developing in the individual integrity of barriers increase, which have resulted in the "Swiss cheese" domino effect associated with the majority of major accidents.

Asset integrity and ultimately process safety can be significantly improved by removing this silo factor through an integrated data management model clearly linked to control major accident hazards - and these days, a lot of this can be done without leaving the desk. 

By providing an embedded asset strategy, focused on data capture and integrated data usage, asset-intensive organizations will see decreased costs across their operations, increased process safety performance and ultimately, reduced risk exposure to people, assets and the environment.



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