Seven Manufacturing Digitization Challenges and How to Overcome Them

Take the first steps toward advanced manufacturing technology integration

Published: Wednesday, July 15, 2020 - 11:01

Artificial intelligence (AI)-powered robots, 3D printing, the internet of things (IoT)... there’s a whole world of advanced manufacturing technology and innovation just waiting for small and medium-sized manufacturers (SMMs) that want to step up their digital game. Unfortunately, manufacturing digitization can present some fundamental challenges, like added cybersecurity risk.

So how do smaller manufacturers increase their advanced manufacturing technology capabilities while balancing the associated risks? Let’s dissect some of the top challenges for SMMs.

1. Cybersecurity plan

All technology implementations should begin with a plan that includes cybersecurity. A sound cybersecurity plan not only helps manufacturers identify and improve current security protocols, it also positions them to manage future risk.

Key stakeholders should identify the most critical information assets to protect, map how that information flows through the organization (currently and with any proposed technology or process changes), and determine the level of risk if that information were lost or compromised.

This sets the foundation for how the company will address risks to that information and can be used to assign risk management roles, develop secure procedures, and implement appropriate safeguards.

2. Available capital

Without a plan, an organization’s efforts to digitize manufacturing operations can lead to unbounded investment costs. This is especially true when considering the cybersecurity aspects of a digital environment, where investments can become reactive if not thoughtfully prepared for in advance. Once a plan is implemented, it enables SMMs to sensibly invest in advanced manufacturing technology capabilities over time to deliver ROI benefits such as:
• Increased operational efficiency and agility
• Reduced downtime
• Improved ability to predict and adjust to facility and supply changes

There’s also the cost of nonadoption to consider when it comes to digitizing manufacturing operations, such as failing to keep pace with competitors or struggling to meet current market expectations. A thorough investment plan considers the cost and benefit to implementing—or not—any changes, when those changes should occur, and how much money to set aside to prepare for those changes.

3. Learning curve

One of the biggest manufacturing digitization challenges is the lack of relevant knowledge to implement advanced manufacturing technologies in a safe and secure manner. But overcoming this learning curve may be as simple as reaching out to external consultants experienced in providing guidance and resources to smaller manufacturers.

Enlisting outside expertise for any kind of technology implementation can help an organization leverage knowledge, skills, and abilities they wouldn’t be able to access otherwise. Outside experts can provide immediate implementation guidance and training to help organizations take advantage of innovations such as the following:
• AI/machine learning
• Advanced data analytics
• Augmented/virtual reality
• Automation
• Cloud computing
• Digital twins
• Sensors/IoT
• Wireless infrastructure
• Zero-trust models

4. Rigid infrastructure

Manufacturing digitization efforts often must overcome existing infrastructures that are rigid and likely incompatible with advanced manufacturing technology capabilities. Digital transformation requires transformation in every aspect of the organization, beginning with training.

Training may include, for example:
• New robotic operations
• Flexible production-line configurations
• Cloud-based resource planning

5. Employee reluctance

One of the most common manufacturing digitization challenges is humans. Human errors create many of the common risks facing organizations, including safety, quality, and cybersecurity risks. For example, humans can:
• Configure machines incorrectly or insecurely
• Forward unprotected, business-sensitive information to outside parties for quoting
• Mishandle equipment
• Open unknown attachments

Digitizing manufacturing may require new processes and retraining on equipment. Unfortunately, humans are especially resistant to change. Where possible, change shouldn’t be imposed. Rather, it should instead be the outcome of a continuous discovery phase that empowers employees to test current processes and identify room for improvement.

The discovery process requires engagement at all levels of the business. It should begin with the company’s president or leader and then continue through key multi-departmental staff, including decision makers at every level of the organization. This process should consider the experiences and expertise of all employees, including but not limited to:
• Administrative staff
• Engineering staff
• IT managers and staff
• Operations managers
• Shop-floor employees

6. Outdated systems

Technology changes at a much faster pace than traditional manufacturing equipment, often with an expected lifespan of fewer than 10 years, and planned obsolescence around three to five years. The older a technology infrastructure is, the more difficult it is to make it compatible with a digitized manufacturing environment.

In a fully realized digitized environment, appropriate data can be shared between a variety of systems. However, if business platforms and technologies are more than five years old, they may not be able to read, write, or share data as needed.

Updating technology can be extremely challenging because numerous interdependencies must be considered. A carefully tested parallel, phased, or piloted implementation approach can be used to upgrade systems without affecting the production line. Leveraging a more modular approach to technology, such as by using standard application programing interfaces (APIs), can reduce these concerns for future innovation implementation.

7. Privacy concerns

Digitization challenges often include privacy concerns because digitized manufacturing capabilities can provide a window into every aspect of a manufacturing operation. Privacy should be considered whenever information is collected that could be used to identify a person. This may include employee or customer contact information as well as the data collected by certain IoT sensors, cameras, or biometric authentication devices. It is important to note that although data from one device might not present a privacy concern, those data combined with data from other devices could.

Taking cybersecurity seriously at the outset will give SMMs the opportunity to protect privacy as well, especially in the following areas:
• Contingency and disaster recovery planning
• Operational security
• Personnel security
• Physical security

Manufacturing digitization begins with a plan

Each of these manufacturing digitization challenges can be addressed with an implementation plan that works with current SMM processes, while enabling future growth opportunities in order to stay competitive. Fortunately, there are resources for smaller manufacturers to take that first step toward advanced manufacturing technology integration.

Helping SMMs step up their technology game is part of the mission of the MEP National Network. With MEP centers located in all 50 states and Puerto Rico, and more than 1,400 trusted advisors and experts at approximately 375 MEP service locations, the network provides U.S. manufacturers with access to the resources they need to embrace advanced manufacturing technology at their own speed.

First published June 25, 2020, on NIST’s Manufacturing Innovation blog.

About The Author

Celia Paulsen

Celia Paulsen facilitates efforts to improve the cybersecurity posture of small and medium size manufacturers throughout the United States as the National Institute of Standards and Technology (NIST) Manufacturing Extension Partnership (MEP) cybersecurity services specialist. She has been at NIST for about 10 years doing research and developing guidance in areas such as cyber supply-chain risk management, small business cybersecurity, and cybersecurity for additive manufacturing. Prior to joining NIST, Paulsen was an analyst for the National Security Agency in the U.S. Army. She has an MBA in information security from California State University, San Bernardino, and bachelor’s degrees in information technology and business management.