IILA x IOTA — Bridging the Gap between OT and IT in Production Metrology

The full article was originally published by Daniel Trauth on Medium. Read the full article here.

Quality Applications in Production Metrology

Quality applications and production measurement technology (referred to as Production Metrology) cover an important market, see Figure 1. In Germany alone, revenues from the manufacture of measuring and testing instruments rose from USD 28 billion to USD 38 billion between 2010 and 2016. According to a statistic by Statista, a further increase to USD 41 billion is expected in Germany by 2020. Although Germany is an important industrial nation, the figure below shows an incredible worldwide potential in the field of quality applications and production measurement technology.

Figure 1: Manufacture of measuring and testing instruments in Germany from 2010 to 2022. Source: Statista 2018, Image: © WZL | Semjon Becker.

In quality applications and production metrology, measured data — referring to the quality of a product — is exchanged between manufacturers (e.g. OEMs) and their suppliers; most probably in a different variety of formats and in a short notice. This non-standardised exchange of quality data is associated with considerable financial losses, because on one hand there is no reasonable exchange standard and on the other hand cooperation between manufacturers and suppliers without exchange standard simply does not work.

In recent years, few attempts for exchange protocols like Quality Data eXchange (QDX) or Advanced Quality Data Exchange Format (AQDEF) have become increasingly common in use. For direct integration of devices into Statistical Process Control (SPC) software, some standards such as the MUX-50 data format are available. However, this is an error-prone process with low trustworthiness.

It is imperative that the measured data should be transferred immutably conforming high data security standards and existing data exchange protocols. With advancing digitisation and globalisation, the use of Distributed Ledger Technology (DLT) as a decentralised protocol can lead to a worldwide backbone for measured quality data, enabling trust, data security and widely useful exchange format. But first, one needs a concept to combine Operational Technology (OT) and Information Technology (IT).

1. What is OT?

Most people are probably familiar with the term information technology (IT). IT professionals usually work on the business side and cover the entire spectrum of computing science, such as software, hardware, communications technologies and related services. However, IT does not include embedded technologies and industrial equipment, so most IT teams have little experience with Industrial Control Systems and are unfamiliar with high voltage currentsProgrammable Logic Controllers, and Computer Numerical Controls. Operational Technology (OT) is a relatively new term and as Gartner explains:

“OT is hardware and software dedicated to detecting or causing changes in physical processes through direct monitoring and/or control of physical devices such as valves, pumps, etc.”

— Gartner IT Glossary, as of Jan. 2019

In general, Industrial Control Systems (ICS) are environments that contain Supervisory Control and Data Acquisition (SCADA) systems, Distributed Control Systems (DCS), Computer Numerical Controls (CNCs) and Programmable Logic Controllers (PLCs). Embedded systems are as much a part of industrial engineering as a variety of devices for scientific data acquisition, data modelling, and data processing.

IT and OT have distinct roles in a company. With the advancement of digitisation and the industrial internet, the boundaries between the two teams are blurring. More connectivity and integration is of course beneficial for intelligent analysis and control. While security has always been a priority for both IT and OT teams in traditional systems, these newly arising networked IT/OT systems represent new scenarios and risk profiles in both directions. Close collaboration would therefore be the ideal solution. However, the two areas still tend to work side by side rather than collaborative. It is precisely why this integration is necessary in order to take advantage of the opportunities offered by IIoT.

The main concern of both parties is to maintain control over systems and machines and ultimately to ensure the safety of their employees and customers. The new solutions should incorporate the following key components to satisfy both sides:

  • Identification and Authentication of all devices and machines in the system, both in production facilities and in the fields, to ensure that only approved devices and systems can communicate with each other. This would reduce the risk of unauthorised and untrusted devices compromising the network and taking control over systems or machines.
  • Encryption of all communications between devices, machines, and operators to protect the privacy of the data being transmitted.
  • Integrity assurance of the data generated by these systems. Intelligent analysis is an important facilitator in the introduction of the industrial internet. But this analysis is worthless if the data itself cannot be trusted.

With the development of distributed ledger technology, a powerful protocol is now available that could bridge the gap between IT and OT in the future.
Using the measuring instruments as an example, which by definition are dependent on data integrity, tamper-proof data and complex measurement calibrations, a proof-of-concept was set up, which is supposed to bridge the gap between OT measuring devices and IT data services via IOTA.

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The full article was originally published by Daniel Trauth on Medium, where people are continuing the conversation by highlighting and responding to this story.

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