A production facility free of malfunctions or stoppages is the dream of every manufacturer and the daily aim of their maintenance personnel. But how to achieve this? The answer lies with today’s maintenance personnel. It is the maintenance personnel of any production facility who have the greatest insight when it comes to that facility, and its devices and components. They are the ones who know a plant’s processes inside-out and who ensure that all of those processes are running as smoothly as possible. This places much responsibility on their shoulders. And if that wasn’t enough, today’s maintenance personnel also need to be able to combine their disciplined skills and knowledge with IoT know-how. Only through this, will they be able to successfully connect multiples systems and automate processes to allow for malfunctions to be detected early-on or avoided entirely. In order for today’s maintenance to be able to rely on smart maintenance, however, the data that they are working with has to be accurate.
Challenges Facing Digital Production Facilities
The challenges facing digital production facilities are manifold. In order for error patterns to be identified and maintenance action to be efficiently planned out, vast quantities of data are required. This data needs to be extracted, collected, and analyzed in order so that IT systems, software and hardware are able to function and work together smoothly. Without this, there is a serious risk of corrupted data inadvertently slipping into a system unnoticed; a situation which could, under the “right circumstances”, have fatal consequences. The process of extracting, collecting and analyzing data also helps to reduce the likelihood of deliberately corrupted data from entering a system. This is important because the act of connecting devices and datasets via the internet makes these once isolated areas obvious targets for cybercriminals.
The Cybersecurity Strategy – Helping You to Fortify Your Digital Production Facility
Unwanted attacks on networks pose a serious risk to digitized production facilities. A production facility that has been brought to a standstill due to malfunctioning/manipulated software or data is the nightmare of every maintenance technician. The best way a company can safeguard themselves against such attacks is to implement a well-thought-out cybersecurity strategy. This cybersecurity strategy would entail such defense mechanisms as firewalls, intrusion detection and prevention systems, honeypots and in-house awareness training for staff. However, even with all of this, it is incredibly difficult for any company to completely safeguard themselves against all potential dangers as there will always be new hacker attacks. Is there a panacea or a single solution available? Unfortunately, there is not. However, if all else fails, a reliable data management system can help a company to weather the worst.
The Connection Between Data Management and Disaster Recovery
Regularly backed up data (e.g. taken from automated devices) can be used for disaster recovery if a cyberattack takes place. Meaning, it enables you to quickly find and restore a previous, error-free version.
Making regular comparisons of project data can also help to identify cybersecurity attacks. This is done by comparing the data running on the device with the data taken from the last backup on the server. If both versions are identical, maintenance staff know that everything is as it should be. However, if differences are detected, this may be an indicator that a cybersecurity attack has occurred. Maintenance technicians may be able to come to a preliminary conclusion concerning the error source based on the way in which the data has been changed. Documenting changes to versions of data plays an important role when it comes to achieving this. It can also help to eliminate any uncertainty involved in determining whether a dataset has been intentionally or accidently changed.
Disaster recovery can only be successfully carried out if the data in question was accurate to begin with. What’s more, carrying out comprehensive and ongoing data backups requires a correspondingly substantial amount of effort. The maintenance technician goes from device to device carrying out backups and comparisons. However, it would be much easier if they had access to a data management system capable of performing all these tasks automatically for them. versiondog is a data management and version control system that allows you to schedule automatic backups and automatically compares versions with the latest version on the server. Authorized changes can be documented without a fuss and unauthorized changes can be quickly detected.