END TO END ASSET MODELLING. DATA TO DECISIONS.

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TAILOR-MADE SOLUTIONS USING ASSET ANALYTICS

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RELIABILITY ENGINEERING CAPTURED IN ASSET MODELS

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OUR ASSET MODELS CAPTURE EXPERT KNOWLEDGE

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END TO END ASSET MODELLING. Data to Decisions.

We are an Australian company that assists businesses operating in asset intensive industries through end to end asset analytical model builds. Our team offers a variety of optimization solutions that are based in reliability engineering. We develop flexible asset models to address all potential risks, asset configurations, operational conditions and environmental conditions that may occur. This is achieved by combining condition assessment, decision making frameworks, detailed system analysis using a Reliability Centered Maintenance foundation, various optimization techniques and corporate value frameworks, into a streamlined, end to end process.

End to End Asset Models. Data to Decisions.

Our asset models uses Reliability Centered Maintenance + Decisions (RCMD) methodology to automate deployment and result generation. Asset modelling identifies the optimal maintenance, operational, intervention and other life-cycle strategies, without the need for internal expertise. Each model is tailored for its unique context and purpose, then optimized for rapid deployment. Asset models are built on a reliability engineering foundation, using expert knowledge and industry-sourced data. Our company maintains a growing library of knowledge, that is continuously improved by subject matter experts.

Our models service companies operating in the mining-, utilities-, oil and gas-, rail and infrastructure industries. We improve and attain speed to market, quality of output and reduction of overheads. Modla provides off-the-shelf asset models and asset modelling services that allow owners to make informed decisions using a repeatable framework and data backed process. Asset modelling entails all components between raw data inputs to decision making outputs, including condition assessment, failure mode analysis, probabilistic analysis, task applicability and optimization of strategy, operation and interventions.

A typical deployment will begin with an introduction session, then data gathering and mapping. This is followed by output generation and validation. Improvements can be made to the asset models as new technologies emerge, or as new data / information becomes available.

MEET OUR EXPERT LEADERS

Dane Boers

Dane Boers is the founder of Modla. He has a dual qualification in physics and engineering, with a background in mining and electrical utilities.

He has accumulated extensive knowledge of investment and asset management, accounting and reliability engineering providing him with the ideal foundation from which to assess the full chain of asset modelling value. Dane now leads the development of Modla’s knowledge base.

Dane Boers Asset Model Leader
Janti Kriel

Janti Kriel has a Master of Engineering in Engineering Management. His areas of expertise are financial modelling, data and asset analytics, as well as optimisation.

He has extensive experience as a management consultant having delivered numerous optimisation and business growth projects across Africa. He has wide-ranging experience across the beverage, FMCG, petroleum and healthcare industries. His analytical and business growth experience position him ideally to drive improvements and create value.

Janti Kriel Asset Model Leader

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