AI-powered robots, 3D printing, the Internet of Things, there’s a whole world of advanced manufacturing technology and innovation just waiting to be discovered for little and medium-sized manufacturers who want to maximize their digital game. However, manufacturing digitization can present some fundamental challenges, like added cybersecurity risk. Let’s examine some of the highest challenges involved in implementing advanced manufacturing technology applications.
In this article we will learn about:
- Cybersecurity Plan
- Employee Hesitancy
- Learning Curve
- Outdated Systems
- Privacy Matters
Cybersecurity Plan
All technology executions should launch with an idea that includes cybersecurity. A solid cybersecurity plan not only aids manufacturers recognise and enhance current security protocols, but it also empowers them to manage future risk.
Essential stakeholders should understand the leading critical information assets to shield, chart how that information flows through the organization with any proposed technology or process changes and determine the value of risk if that data was lost or jeopardised.
This sets the inspiration for a way that will address risks to its information and assign risk management roles, develop secure procedures and implement appropriate safeguards.
Employee Hesitancy
One of the foremost common manufacturing digitization challenges is humans. Human errors represent one among the foremost common risks facing organizations, including safety, quality, and cybersecurity risks. as an example, humans can:
- configure machines incorrectly or insecurely;
- forward business-sensitive information to outside parties for quoting;
- mishandle equipment or
- open unknown attachments
Digitizing manufacturing may require new processes and re-training on devices. Unfortunately, humans are especially proof of change. Where possible, the change shouldn’t be imposed. Rather, it should instead be the result of an eternal discovery phase that empowers employees to check current processes and identify room for improvement.
The discovery process requires engagement at the least bit levels of the business. It should begin with the company’s president or leader so continue through key multi-departmental staff, including decision-makers at every level of the organization. This process should consider the expertise of all employees, including but not limited to administrative staff, engineering staff and IT managers.
Learning Curve
One of the most important manufacturing digitization challenges is the lack of relevant knowledge to implement advanced manufacturing technologies in an exceedingly safe and secure manner. But overcoming this learning curve could also be as simple as reaching external consultants experienced in providing guidance and resources to smaller manufacturers.
Enlisting outside expertise for any quite technology implementation can help a corporation leverage knowledge, skills, and skills they wouldn’t be ready to access otherwise. Outside experts can provide implementation guidance to assist organizations cash in of innovations like the following:
- AI/machine learning
- Advanced data analytics
- Augmented / video game
- Automation
- Cloud computing
- Digital twins
- Sensors /IoT
- Wireless infrastructure
- Zero-trust models
Outdated Systems
Technology changes at a way faster pace than traditional manufacturing equipment, often with an expected lifespan of fewer than 10 years and planned obsolescence around 3-5 years. The older a technology infrastructure is, the tougher it’s to create it with a digitized manufacturing environment.
In a fully realized digitized environment, appropriate data is shared between a spread of systems. However, if business platforms and technologies are over five years old, they will not be able to read, write, or share data as required.
Updating technology will be extremely challenging since numerous interdependencies must be considered. A carefully tested parallel phased, or piloted implementation approach will be wont to upgrade systems without impacting the assembly line. Leveraging a more modular path to technology, like by using standard application programming interfaces, can reduce these anxieties for future innovation implementation.
Privacy Matters
Digitization challenges often include privacy concerns, as digitized manufacturing capabilities can provide a window into every aspect of a producing operation. The privacy should be considered whenever information is collected that might be accustomed to identify someone.
This may include customer contact information similarly because of the data collected by certain IoT sensors, cameras, or identity verification devices. it’s important to notice that while data from one device may not present a privacy concern, that data combined with data from other devices could.
Taking cybersecurity seriously at the outset will give the chance to shield privacy also, especially within the following areas:
- Contingency and disaster recovery planning
- Operational security
- Personnel security
- Physical security
Each of those manufacturing digitization challenges is addressed with an implementation plan that works with current processes while enabling future growth opportunities to remain competitive.
Helping companies and budding manufacturers intensify their technology game is an element of the mission of Dainsta. If you are interested to read more on similar manufacturing topics, you can check out our other fascinating blogs here.
