Phil Crothers marshals Boeing toward the next industrial revolution

Phil Crothers

Technical Fellow who leads Boeing’s research investment strategy for materials and manufacturing technology.


Boeing is actively investing in technologies to enhance the quality, safety and efficiency of the production system—including the supply chain—through the entire product life cycle.

By Candace Barron, Boeing writer | Photography by Barbara Freeman

Q. How is Boeing preparing to lead in the future of aerospace manufacturing?

A. As an enterprise, we are investing in technologies for productivity, safety and quality, and creating what we call the One Boeing Production System. We are developing composites technology, such as thermoplastics and high-rate processing, as well as metals machining. We are continuing extensive investment in automation to get people out of dirty, dull and dangerous activity, like drilling and fastening. We are also extending human performance with virtual and augmented reality (VR/AR), as well as human collaboration technologies like cobotics and exoskeletons. Automated finishing and coating removal are also highlights in development. Our efficiency in implementing all of these technologies will be a key.

Digital technologies are forming a large proportion of our efforts in additive manufacturing, process control and machine learning. Along this line, it is our internal use of model-based engineering, Industry 4.0 technologies, and revolutionizing our supply chain, which will really see us lead the competition.

Q. What does Industry 4.0 mean to Boeing, and what steps are being taken to prepare the business to lead in the future of manufacturing?

A. Industry 4.0 has had many names, depending on which region of the world you are in. In some cases, it has had the stigma of being this all-encompassing trend that will deliver miracles. So we’re paying close attention to where the real value is.

At Boeing, Industry 4.0, also called the Fourth Industrial Revolution, will enable the convergence of physical and digital systems. This will cause massive transformations in the way we design, manufacture and service our products, and the ways our customers operate them. It’s bringing together traditional manufacturing and design tools such as computer-assisted design and building information modeling, data management and physics-based simulations, and connecting physical assets through the Internet of Things to enable product lifecycle management.

In manufacturing, we are piloting several projects to help us find the key areas of value. These are the digital and systems architectures that will help us be successful locally, and then able to scale quickly. For example, with computing power and artificial intelligence technologies, such as machine learning, we can extract valuable patterns from complex combinations of the many influences on the quality or productivity of our manufacturing processes. These are patterns that would not be exposed by manual methods. By capturing these patterns or machine-learning models and implementing a closed loop of control, we can enhance our operations in real time, while also capturing data that can be run in future design loops. In another example, Industry 4.0 also transfers directly to our management of the supply chain, enabling real-time connection across the globe for reporting, collaboration, control and recovery from disruption.

Q. What are the risks and rewards of being an early adopter of Industry 4.0 technologies?

A. There are many risks, but the benefits are potentially huge. Behind the risks are questions like, how much will it cost us to extract and exploit necessary data? How long will it be before we see the required benefit from new methods, or will it be more efficient to use contemporary methods of control and process management? What are the right things to control with these technologies? How do we know if we are actually capturing the critical parameters for control of processes?

And then there is the need to choose the right data to use, source and/.or store; what are the formats of data we need; can we reuse one method for a second application or do we have to reinvent for each implementation

But if we can successfully answer these questions, the benefits of delivering and analyzing the right data means we can immediately multiply the skills of our workers; vastly improve our equipment and process productivity and quality; and potentially know of, predict and correct our supply chain disruptions in real time.

Other industries have been investing and leading the way with remote command centers of global production systems and supply chain. We are actively collaborating with other companies to share learning in this new field.

Q. How can companies protect their intellectual property or competitively sensitive data with a digital thread that extends to both suppliers and customers?

A. People need to trust Boeing. And thanks to our experienced information technology teammates, they can. It is more than a brand; our investments in cybersecurity reflect that. Some of the everyday controls protecting data include access controls, encrypting data, end-point protections and incident response. I’m always staggered to hear the number of emails coming into Boeing that are categorized as spam or malicious that are blocked.

Cybersecurity is one of the major investments that must be made as a part of any contemporary technology development involving digital data. A prime example is the protection of build files for 3D printing in remote machines at customer or supplier facilities. There is potential for IP escapes, counterfeit parts, build package corruption and printing beyond the authorized number of parts.

Many developments, including blockchain, secure digital rights management, data delivery streaming and decryption at the machine, are being developed. This will make certain the parameters of operations and vital design intellectual property are contained in approved or certified channels, not reused or corrupted, and that only the designated machine is used for production.

Q. What standards need to be established so that Industry 4.0 technologies can be broadly replicated, and who is working to establish them?

A. The fundamental purpose of Industry 4.0 is to facilitate cooperation and collaboration between technical objects, which will require an unprecedented degree of system integration across domain borders, hierarchy borders and life-cycle phases. An Australian government report recently cited 22 relevant standards committees within the International Organization for Standardization (ISO) alone, including Information technology, software and systems engineering, safety, Industrial data, robotics, and security and resilience groups.Within Boeing, we have many groups working in data standards, including making proactive decisions on adopting existing standards, developing our own internal standards, monitoring external standards development and participating in external developments. Boeing, as a part of the global community, is working closely to try to smooth this path.

Q. What methods can the business use to improve the implementation of technologies?

A. The continued uptake and refinement of readiness levels, such as MRLs (Manufacturing Readiness Levels) are key, with their greater emphasis on early alignment and integration significantly lowering the risk of transition to the customer’s engineering, production system and business operations.

The company is also continuing to improve methods of production hardening. We have different constraints to other industries; because of the high value of our products, physical demonstration is prohibitively expensive. So, unlike automotive, for example, we can’t afford to physically prototype hundreds of parts before entering production to prove our new technology inclusions. Once again, digital advancements are key. Simulation tools and digital twins are becoming more and more powerful to minimize the gap between our physical world and our model-based engineering. Developing tools that combine our physics-based models and machine learning models, based in production data, can be used to directly analyze our engineering models. This allows us to minimize our risks at the design stage. Through these methods we can ensure technology will work in operation the first time.

    Robots at work

    Robots at work

    Boeing technologists work to integrate new automation tools into the production systems.