WHAT ISSUES AND PROBLEMS CURRENTLY EXIST IN THE INDUSTRY?

Let’s look at some of the problems we already know about:

• Underperforming assets account for approximately 30% share of operating expenses

• Repair and maintenance costs increase by 10 – 15% yearly.

• $4 of profit is lost for each $1 spent on repairs.

• Every third maintenance and repair activity is unnecessary

• Working staff spend less than 4 hours daily on the direct execution of work

• 50% of industry employees will retire in the next seven years.

INFLUENCES AND MEGATRENDS

Our approach is influenced by leveraging several mega-trends impacting most asset-intensive operations.

• The transition from human-based decisions to digital machine-assisted decisions

• The gig economy where personnel do not stay in the same job for long

• The transition to sustainable and renewable resources means that traditional life cycle asset management has additional complexity and constraints

• The rapid increase in new technologies and methodologies forces organisations to embrace change or risk obsolescence.

These mega-trends drive towards increased use of digital technologies to support faster decisions and sustainability within increasingly complex environments and constraints.

Hence Asset Management needs to accommodate: 

• The increasing use of digital technologies to support physical asset management

• The ability to use short life-cycle digital technologies (due to speed of innovation) with long life-cycle physical assets (due to maximising life-cycle value from investments)

• Customisation of management processes to fit the actual operation, and

• The provision of systems that have high adoption rates via low cognitive loads. 

The quality of the data used by the digital tools and the humans is the key to making digital machines better decision makers. A key element of our solution is the design and governance around quality data and structures to support the collaboration between digital devices and humans, as well as providing for “Explainable” Artificial Intelligence.

BEST OF BREED SOLUTIONS

We are putting forward several best-of-breed solutions that can interoperate with each other and your existing enterprise systems in a vendor-neutral ecosystem. Our experience in delivering such solutions allows us to adapt to the customer’s requirements as they progress through the APM journey and maturity without impediment.  We do this by packaging a fully outsourced APM solution to a fully insourced solution with the ability to transition to different levels without restriction.

SENTIENT SYSTEM COMPONENT

More information at Sentient System

Sentient System is a decision support and real-time optimisation platform for asset-intensive operations. It uses a self-learning digital twin of a process to provide for model-based decisions. The key to the technology is to automatically maintain alignment between the physical plant and the digital representation of the plant.  The system monitors the fundamental changes in performance and asset consumption, continuously calibrates the digital twin by sophisticated machine learning and uses this self-calibrated digital simulation to provide:

• Detailed asset health and performance at a component level

• Precise and quantified system impact from changes to asset health and performance

• Predict future behaviour based on historical behaviour changes

• Early warning when the expected behaviour does not align with the predicted behaviour indicates an increased risk to the operation as a component within the system has changed its behaviour

• Real-time optimisation by simulation and manipulating the digital representation of the plant to find improved operation from a production or asset consumption perspective. Once optimised in the digital world, execute the changes to the real-plant and ensure the actual change aligns with the expected improvement.

While the Sentient System platform is primarily a whole-of-system and whole-of-life optimisation of asset-intensive operation, it has many tools and a flexible pricing model to support APM at all maturity levels.

• Library of Assets with self-learning algorithms and failure modes

• Advanced pattern recognition 

• Comprehensive fundamental modelling capabilities in mass, energy and value transfer and flow, asset consumption, and asset damage.

• Comprehensive empirical modelling and machine learning capabilities.

• Comprehensive predictive maintenance capabilities

• Interpretive analysis of condition monitoring data 

• Data structures to support explainable AI 

• Extensible data analysis capabilities 

• Extensible data visualisation capabilities 

Sentient System has been deployed and proved as an APM solution to different maturity level organisations with a very high return on investment in all cases (5 – 10 times).  

ODBOK METHODOLOGIES

More information at www.odbok.cloud

Within an interoperable digital ecosystem, the quality of data and alignment of data structures is paramount between all the digital service providers. While each vendor has its own data structures and ways of ensuring the quality of the data used, a methodology to support all vendors and solutions reduces the effort required and improves the quality of a combined solution. It also provides for the addition of new vendors into the ecosystem with minimal rework.  

Odbok Pty Ltd was established to assist companies to align, integrate and industrialise the data within their systems in readiness for Digital Transformation and Industry 4.0 Automation initiatives. 

We do this by:

• Maintaining a technology agnostic reference architecture.

• Continuous optimisation of our Data Foundation Methodology

• Collaborating across multiple disciplines and sharing outcomes with our customers.

• Maintaining our focus on ensuring high-quality data outcomes for our customers.

• Leveraging the years of experience and knowledge across our SMEs.

The Odbok Methodology is a Systems and Data Lifecycle methodology, and it will be refined specifically for the customer to encapsulate their objectives and constraints. The Odbok methodology is designed to be implemented in either a greenfield or a brownfield situation, enabling the customer to determine the pace at which remediation and alignment occur. It orchestrates project and maintenance changes across all systems to maintain the integrity of business objectives, compliance, and operations data.