Maintenance Data

We are an IT company specialized in data management, analysis, and development for the maintenance industry.
we work with large crude datasets to obtain information out of them, and work with information to create data.

Data transformation

While decisionmakers follow the fashionable and shiny buzzwords, maintenance below all the layers of abstractions and KPIs remain basicly the same: we try to keep our equipment in a functioning condition.
The most primitive data acquisition is non-instrumental inspection, and it gives a somehow reliable data: the experienced maintenance personnel puts their hand on the equipment, push a scredriwer against the housing and and obtain vibration and heat information, or just look at the equipment with expert eyes (aka visual inspection).

This information was hard to convert to data, therefore we came up with trillions of sensors to measure all that is measurable, and created datasets that need to be transformed into information.

• Transforming data to information requires specific knowledge of the reality behind the data. The only difference between correlation and causality is the knowledge how certain data are and are not connected.
• Transforming information to data requires specific quantification knowledge to classify the human readable information into comparable data.

Information storage

Maintenance information storage has two main challenges: it has to ensure comparability to support decision making and has to be well structured to ensure reusability of the data in all fields. Any dataset is just as valid as well it was defined, and as well as it was entered.

50 years after the first CMMS systems it seems to be absurd, but even in the 32st century we are fighting with the same problems as before any computarization: instead of opening the log book, now we open the shiny logbook, and try to figure out what the last man who filled out the same fields meant when wrote it. We are trying to understand failure notices from production, and the action recorded by maintenance, and try to figure out, where is the maintenance issue.

Services

• Data Transformation as long-term systems or single project data:
  • from information to data
  • from data to information
• Systems:
  • databases for specific purposes
  • software systems for specific data storage, conversions and reporting