Our team our highly motivated and have a great education in relevant engineering, science and business systems. We are educated to Masters and PhD (Doctoral) level in Physics, Natural Sciences, Computer Science and Reliability Engineering with Masters of Business Administration.
We see an explosion in the global business world of "digitalisation" and the race to adopt Artificial Intelligence (AI). The problem is many are heading straight into this area without understanding the safety and reliability engineering principles, inasmuch with complexity of digitalisation and AI there comes an exponential rise in the variety and severity of failure consequences. This is not good to business nor humans.
We set out to address this complexity by analysing the systems under which AI and Digitalisation has been identified and run deep analyses to ensure all failure causes are defended against - by this, it means we as humans are still in charge of Artificial Intelligence and also we improve the safety and reliability by ensuring these failures modes (failures causes) are again, defended against.
Artificial Intelligence includes techniques such as Machine Learning (ML) whereby algorithms self learn over time with masses of data obtained from the machine. This is not a simple solution and will not bring about machine reliability alone by predicting when it will fail in the future. The idea is, it will predict how much life is left and alert the operator to say "please help me and give me medicine or replace a part for me, or else I will breakdown" which could mean varying consequences from safety consequences such as death to economic consequences which means loss of income due to a machine breakdown.
Many companies are unwittingly being sold many contracts to install machine sensors for AI/ML by the machine manufacturer which is not always in the interests of the Operator because these sensors, although fairly cheap, it is the analyses that is very expensive and as such creates revenue streams for the machine manufacturer and not the Operator so these contracts are not really in favour of the operator. We want to change this too. By doing so we help the operator, owner and general public by making the machines safer and reliable.
Our MRCM (Marine Reliability-Centred Maintenance) Platform stops all this and actually improves safety and reliability using the most cost effective method available through Decision Logic Trees, Binary Decision Diagrams, Fault Tree Analyses and other techniques that are qualitative and quantitative that is also scalable meaning we can cover more and more machines far quicker and hence generate more income and profit and thus help more and more machines and companies and essentially the greater good for us humans now and in the future.
We have called it Marine Reliability-Centred Maintenance Platform - because we will start our business in the Marine world including offshore Oil and Gas because it is here that the public rely on 90% of goods transported by ships which means we get our products delivered on time and on safe and reliable Ships and Oil and Gas and Renewable Energy because it generates the public's energy needs.
We have more literature to share. We have a website at www.relmar.co.uk but this is presently undergoing reconstruction. We are based in Hull, East Yorkshire, UK and open for presentations.