Mirce Science Philosophy
The development of science started when people began to study phenomena not merely observing them. People developed instruments and learned to trust their readings, rather than to rely on their own perceptions. They recorded the results of their measurements in the form of numbers. Supplied with these numbers they began to seek relationships between them and to write down in the form of formulas. Then the formulas became the only things they came to trust when they began to predict things they could not physically experience.
The philosophy of Mirce science is based on the premise that the purpose of existence of any machine is to do a work, which is considered to be done when a measurable function is delivered through in-service time. It is measured by quantities deliver, like: miles travelled, number of units produced, quantity of energy supplied and similar. However, experience teaches us that at any instant of in-service time there is a chance of the work being interrupted by occurrence of compelling events caused by: natural phenomena, human conscious/unconscious actions or their interactions. Consequently, for the work to be continued it is necessary to take recovery actions like: performing required maintenance tasks, change the mode of working, select new location and so forth.
To enable quantitative prediction of the work done by machines during the in-service time, Dr Knezevic introduced the concept of functionability, which is defined as a probability of delivering measurable work at instant instant of time. Consequently, from a functionability point of view, during their in-service reality machines could be in one of the following two states:
- Positive Functionability State (PFS) – work is being done
- Negative Functionability State (NFS) – work is not being done.
The motion of machines through in-service reality is a physical manifestation of the impacts of compelling mechanisms that are classified as following:
- Positive Functionability Action (PFA), a generic name for any natural process or human action that compels a machine to move to a PFS
- Negative Functionability Action (NFA), a generic name for any natural process or human action that compels a machine to move to a NFS.
The motion of machines through in-service reality is manifested through occurrences of functionability events that are classified as following:
- Positive Functionability Event (PFE), a generic name for any physically observable occurrence that signifies transition of a machine from a NFS to a PFS,
- Negative Functionability Event (NFE), a generic name for any physically observable occurrence that signifies the transition of a machine from a PFS to a NFS.
Consequently, at any instant of in-service reality a machine can bue in one of two possible functionability states, namly PFS and NFS. Thus, working performances of machines through in-service reality are uniquely defined by the trajectory they generate through Mirce space, which consists of: continuous in-service time, discrete states of a machine and probability of being in that state.
Axioms of Mirce Science
Axiom 1: A machine enters Mirce space in the positive functionability state.
Axiom 2: A machine stays in a given functionability state until compelled to change it by any imposed action whatsoever.
Axiom 3: A functionability event is an observable occurrence at which a machine changes a functionability state.
Axiom 4: Functionability events are occurring with a probabilistic regularity.
Axiom 5: A machine exists Mirce space in the negative functionability state.
These axioms are the bedrock for all predictions in Mirce science. Also, they limit its applications as they do not cover all aspects of in-service reality of machines, like:contracting, marketing, insurance and many others.
The pattern generated by the motion of machines through functionability states during in-service reality forms the functionability trajectory, which is uniquely described by Mirce Functionability Equation.
Mirce science
Generally speaking, the Mirce Science is a theory for predicting the motion of machines through in-service reality, by subjecting mechanisms of causing actions to Mirce Functionability Equation, Knezevic (2014). It is an infinite sum of multi-dimensional convolution integrals that predicts the probability of a machine type being in PFS ate any instant of in-service time. expected work to be done by each machine type. Thus, the same equation, when applied to the same machine type expected to be exposed to different in-service reality (operational, maintenance and support) generate different functionability trajectories through Mirce space, generating different working performances and consuming different resources.
The practical applications of Mirce science is a creation of framework that enables quantitative comparisons of all feasible options and the selection of the machine configuration with the highest probability of success.