The manultimate industry has been significantly impacted by the growing technological advancement of the industrial revolution in the digital era. Smart manufacturing has emerged due to the IoT, AI, and big data analytics technologies that are able to connect all aspects of the production line. It has helped the manufacturers to change, improve operation, productivity and overall quality of the products manufactured. But convenience of these technologies poses a greater threat of cyber incidents. That is why cybersecurity is critical as to avoid interruptions in the functioning of smart manufacturing systems.
This paper seek to address the following research questions:
Although Smart Manufacturing System (SMS) can be described as the convergence of advanced information and manufacturing technologies to implement intelligent manufacturing systems that are self-organized and coordinated to manage manufacturing processes. These systems involve the monitoring of events and flow of information in business processes so as to be able to make informed decisions as well as improve on the rate of production.
Key components of smart manufacturing include:
IoT Devices: Machinery monitored by sensors and actuators send information related to the performance of equipment, the state pf the surrounding environment and the production process.
Big Data Analytics: Sophisticated big data analytical techniques are used to analyze large database and predict when some piece of equipment should go for a maintenance and how the operation could be made more efficient among other things.
AI and Machine Learning: Random data is assessed to incorporate artificial decision-making processes timely, and it also makes results more accurate in terms of quality and supply chain.
Cloud Computing: They enable data to be stored, computed and even accessed from any geographic location and or organizational unit.
Automation and Robotics: Robots and automatic systems are used for repetitive work with the lowest possible margin of error.
The Challenge Which is Increasing in Proportions: Cyber Threats
vnerable’; Manufacturing systems are rapidly integrating into networks and using digital technologies, thus making them prone to cyber threats. Smart manufacturing systems are targeted by cybercriminals for different reasons such as, monetary benefit, theft of intellectual property, and spying on competitors.
The consequences of a successful cyber attack can be devastating:
Operational Disruption: Logical attacks can slow down production lines and thus work stoppages and huge losses.
Data Breaches: Susceptibility to intrusion and leakage of important information like; trade secrets and customers’ data can cause great losses in terms of reputation and fines.
Equipment Damage: Malware can control the settings of a machinery and bring about physical changes and thus affect the machinery negatively and an expensive affair will have to be carried out to fix the issue.
Safety Risks: In this aspect, security breaches lead to risks to the safe operations of equipment and potential accidents among the workers.
In the selection of a source, there is a priority focus on cybersecurity in smart manufacturing, as it is the basis of each technological system.
Due to the likelihood of aforementioned threats, the implementation of strong cybersecurity measures in smart manufacturing is highly desirable.
Here are several key reasons why cybersecurity is essential:
Protecting Intellectual Property:
Smart manufacturing systems create and accumulate considerable amounts of data and information that constitute intellectual property: drawings, designs, production procedures, and recipes. This information should not be compromised and this is the reason why organizations have put in place measures like encryption and access controls.
Ensuring Operational Continuity:
Terrorism activities through cyber attacks are likely to slow down the production process, thus resulting to losses. Life cycle management measures and actions like use of a secure network segmentation, intrusions detection systems, and systematic security review and assessment facilitate a manufacturing firm’s operations continuity.
Maintaining Data Integrity:
Data accuracy and credibility are crucial in smart production to ensure that managerial decisions are wise. Data security encompass measures such as encryption of data, secure methods of communication and data backup to make sure data is not manipulated in a wrong way.
Safeguarding Worker Safety:
Automated machinery and robotics which are used in smart manufacturing systems are in most cases potential dangers if they get into the wrong hands. Security measures for example acquitting controls, protection against intrusions, as well as regular security audits assist assure the safety of the workers by avoiding cases of illegitimate control and manipulation of equipment.
Compliance with Regulations:
Some of the industries have set regulatory measures of cybersecurity that have to be observed by the manufacturers. Mentioned regulations should be followed and strong cybersecurity measures’ implementation will prevent potential legal and financial consequences.
Implementing Effective Cybersecurity Measures
Thus, for protecting existing and developing new smart manufacturing systems, the manufacturers have to understand five levels of protection and risks involved in cybersecurity.
Here are some essential measures to consider:
Conduct Risk Assessments:
Other imperative things to do include: Frequently determine the threats of cybercrime on smart manufacturing systems. List points where the company may be exposed and establish a risk priority ranking of the possibilities.
Implement Access Controls:
Control access to sensitive systems and information only to the employees who need that information for work. Employ aspects such as MFA, RAC, and SP to increase the level of access security.
Encrypt Data:
Secure communication between the different modules and databases as well as data stored in databases and data files. Encrypting data with high encryption algorithms should be implemented and keys should be changed often.
Secure Network Architecture:
Network segmentation should be put in place so as to limit the access of the other part of the network to the critical systems. Implement firewalls, IDS and VPN as they will help in protecting traffic that transverses through the network.
Regularly Update and Patch Systems:
Always update all the system’s software, firmware, and hardware with security patches. Continually update the antivirus as well as anti-malware programs to ensure you deal with newer threats.
Monitor and Respond to Threats:
Trace log and monitor the network and systems’ activities on a consistent basis. Employ security information and event management (SIEM) systems to avert any risk that may be on the rise in the system.
Employee Training and Awareness:
Education and creating awareness of the employees on the criticality and importance of observing the security policies. Employ constant training security sessions for the employees as a way of educating them on security threats and measures to be taken in the future.
Develop an Incident Response Plan:
It is necessary to create an extensive just-in-time action plan in order to act swiftly and correspondingly to cybersecurity threats. They should contain measures outlining how attacks are detected, prevented, isolated, eliminated, and the ways employed to bounce back from the attacks.
Cognitive security: Real-time control systems; Manufacturing and automation; Smart, connected; Definition of Smart Manufacturing; Conclusion
And as the concept of smart manufacturing carries on against the passage of time, so will the security issues of its domain. Companies must defend themselves and be ahead of hackers’ schemes in the modern manufacturing industry.
Emerging technologies such as AI, machine learning, and blockchain hold promise for enhancing cybersecurity in smart manufacturing:
AI and Machine Learning: The use of AI algorithms can search through exponentially large sets of data to determine previously unseen patterns and discrepancies, which helps prevent or minimize a threat. This was a strong point of machine learning models in cybersecurity as it propelled the enhancement of cybersecurity measures based on the new threats obtained from the models.
Blockchain Technology: Blockchain, on this context, can offer an alternative platform for recording and storing the transactions which can increase the reliability and security in SMMS.
Zero Trust Architecture: Thus, for zero trust, every device and user has to be validated before they can be granted access to any resources. It reduces the threats of having insider attackers who compromise the system and move laterally to other areas in the network.
Conclusion
Hence, cybersecurity is more of a necessity in today’s smart manufacturing industries. Preserving confidential information, guaranteeing the business’s continuity, safeguarding the workers, and meeting the regulations are some of the important factors that have to be considered for cybersecurity in smart manufacturing systems. Through the application of strong security measures and proactive strategies against new threats, the manufacturing sector can leverage on SM while avoiding the nasty impacts of cyber crime. Jain Software is dedicated to assist the manufacturers in realizing these objectives including through safe and efficient IT security strategies and techniques specific to the manufacturing sector.