IIoT and maintenance webcast: Your questions answered
The fourth webcast in the CFE Media Industrial Internet of Things series, entitled “Preventive Maintenance: Technologies, Applications and Business Models”, was presented live on Oct. 19, 2017 by Alex West, Principal Analyst, Smart Manufacturing & Industrial Communications, IHS Markit. The webcast can be found on the archive sites at www.plantengineering.com and www.controleng.com.
There wasn’t time to address all of the questions from the webcast’s attendees, and West has supplied written answers to some of those questions:
Q: How can data security and privacy be best addressed?
West: The issue of data security is a significant hurdle for end-users transitioning to IIoT, as should be the case. As more devices are connected, this increases vulnerabilities and the “surface area of attack”. The field of cybersecurity is still challenged by levels of investment that fall well below desired rates, as well as misconceptions in the market. Some of these are:
Having no physical connection to the outside world is a complete fail-safe approach to cybersecurity: cybersecurity requires a holistic “defense in depth” approach, which extends beyond just networking outside of the four walls of a plant to, correct policies and procedures for people, devices and assets, networks etc.
Security by obscurity: Some companies consider themselves to be less of a target due to their anonymity. However, the “success” of recent ransomware viruses such as NotPetya highlight that anyone can be impacted
The cloud isn’t a safe place for data: This is an on-going challenge for many vendors that initially introduced predictive maintenance solutions hosted on a remote cloud. Many of the recent high profile cyber-attacks have succeeded through leveraging vulnerabilities in old and no longer supported operating systems (such as Windows XP). Whilst there are still a large number of manufacturers running outdated OS’s this is not the case when considering leading cloud service providers.
Q: Would you please talk about virtual reality and augmented reality and their implementation benefits on maintenance strategy?
West: The use of these technologies is being increasingly discussed in the industrial space, especially as the industry is faced with the challenges of a retiring workforce and the subsequent loss of skills and knowledge. Whilst virtual reality (VR) has received more attention as a result of its entry into the gaming market, IHS Markit believes the bigger opportunity in manufacturing is with augmented reality (AR).
Imagine a junior engineer using an AR headset supporting both a camera and an audio feed. Faced with a problem they can’t solve, the engineer can “dial-in” a remote colleague (third party support) who can look at the equipment remotely, and provide both visual guidelines (i.e. marking a point on a piece of equipment that needs to be adjusted) as well as verbal support and training, all in real time.
OEM’s can also develop repair and replacement manuals that can be downloaded by workers on location to walk them through the necessary steps.
Predictive maintenance solutions also have the potential to help companies combat a lack of engineering skills. Better information on which assets are near failure and when failure is predicted will help more efficient and effective maintenance planning. No longer will engineers have to review the performance of optimally performing assets and companies can plan and prioritize their maintenance hours to failing equipment. Not only will this reduce downtime, but also rationalize maintenance work, and reduce replacement of non-faulty equipment.
Q: How important is the cloud in supporting monitoring asset health?
West: The use of the cloud will depend on the level of data and analytics required. More recently, companies have started to introduce Edge devices, which can support simple analytics of data either on or near device (for example, a motor with some sensing and processing integrated). This can be used to provide some basic monitoring of an assets health, flagging early indicators of an impending asset fault.
However, to benefit from some of the more complex analytics solutions being developed requires not just more powerful (and so processor intensive) algorithms, but often also large data sets. As the size of these data sets grows decisions based on analyzing data locally or having data hosted by a cloud service provider becomes a more pertinent issue. With predictive analytics asset failures can be forecasted, giving staff the opportunity and time frame within which to repair or replace before unplanned downtime occurs.
As companies look to implement these more complex predictive analytics solutions (and in the longer term prescriptive analytics), and as company’s comfort levels with placing data in the cloud increase, IHS Markit expects the cloud to be central to many asset health services and solutions.