Editorial Note: This is a guest opinion article submitted by Deloitte, compiled by the following authors:
- Myke Miller, Managing Director and Dean of the Deloitte Cloud Institute, Deloitte Consulting LLP
- Mahadev Satyanarayanan (Satya), the Carnegie Group University Professor of Computer Science at Carnegie Mellon University and Deloitte Cloud Institute Fellow
- Diana Kearns-Manolatos, senior manager, Deloitte Center for Integrated Research
Global industrial supply chains and the aviation industry have been significantly impacted during the pandemic. Industrial and manufacturing organizations have seen tremendous stress on personnel, production, and distribution of products and parts. Airlines have faced financial pressures with reduced global travel and changing regulations driving a need for innovation everywhere from the factory floor to the flight. Organizations have begun to address these challenges with a new era of digital lean manufacturing.
However, these solutions focus largely on cost reduction and quality improvement of existing infrastructures rather than the systemic transformation the aerospace, manufacturing, and industrials industries would need to survive, compete, and change/disrupt. Therefore, an ecosystem strategy, which brings together the full business complemented by a digital ecosystem of cloud, edge, mobile, and other platform technologies (e.g., robots, IoT, etc.) can help provide these organizations with a more distributed infrastructure to power a range of solutions, “industrial troubleshooting” infrastructure and application innovations to address these challenges.
As we discussed in our recent interview, “The next chapter in computing is going to be about the creation of this edge computing infrastructure worldwide to enable brand-new, edge-native applications you simply couldn’t create if you only had to rely on the cloud.”
We’ll explore three of these use cases for aerospace across manufacturing, maintenance and customer experience, and mobility–with actionable recommendations on how to take forward these cloud-edge solutions.
Three Use Cases for Cloud-edge Solutions in Aerospace
Advanced Manufacturing and Supply Chains
One of the key trends shaping up in the last couple of years and accelerated by COVID-19 is the shift from a linear supply chain (discrete progression from design of aerospace parts, source, make, and deliver) to a dynamic, interconnected digital supply network (DSN) supported by cloud solutions. The core advantage of DSN is that it incorporates information from different ecosystem partners (that touch six million or more parts that go on an aircraft) to create a virtual world that mirrors the physical world and helps drive informed production and distribution. The result is a more agile value chain that can adapt to changes in product designs and production levels and is overall better prepared for future contingencies.
Aerospace companies are increasingly leveraging advanced manufacturing technologies on the factory floor by using mobile, edge, cloud, and continuously reporting sensing platforms to gain greater predictability and control over supply chains during times of uncertainty. Organizations that produce parts and products for aerospace companies are using everything from robots to 3D printers and digital twins to speed up production, simulate and test scenarios, and drive more data-driven actions across the factory floor.
“This is something that people are doing now, and 86 percent of manufacturers from a recent MAPI and Deloitte survey believe that smart factory initiatives are going to be a main driver of competitiveness over the next five years,” says Lou Librandi, principal, Deloitte Consulting LLP.
One aerospace company, for example, developed a cloud AI platform to better schedule machining assets and direct labor, as well as track inventory The solution used localized data, integrated with ERP and 3PL systems, to monitor “machine available for perform work,” tracking and tracing where parts were in the facility for staging. The organization then developed a command center to manage the factory floor across human teams, allowing the organization to reduce the time spent locating parts in its factory by one-third, and thus, increasing production speed and profitability.
Another example is an Industry 4.0 immersive center—one focused on bringing together advanced manufacturing methods and technologies. The Wichita State University Smart Factory—a 60,000 square foot smart building on a smart grid— offers an experience in which the digital, physical, and experimental come together to speed up smart factory capabilities. Additive manufacturing, collaborative robotics, advanced materials and composites, automation, reverse engineering, and augmented and virtual reality (AR/VR) prototyping simulators are all at the ready on this innovative campus.
Maintenance and Customer Experience
Airlines have a number of customer-facing processes where strong digital solutions can simultaneously enhance processes and the customer experience. Existing cloud solutions power everything from digital flight booking solutions to management of ticketing and boarding passes across a local and global network of flights. However, many aerospace companies still struggle with optimizing the customer experience at the airport and managing a vast network of planes, cargo, and personnel needed to manage each flight.
One of the areas where customer experience can be negatively impacted is flight delays. Here, cloud-edge solutions can help to better manage airplane maintenance (people and parts) to reduce one of the top causes of flight delays. For example, when an aircraft is delayed at the gate, the airline might use a mobile-IoT-edge-cloud network to diagnose the hardware issue using sensors, notify the closest maintenance team based on their mobile location and proximity to the plane, and track data related to the incident to predict future maintenance needs. The airline could potentially benefit from streamlined operations, reduced delay time, and valuable data for future analyses. The business potential here is significant, given the average 1-hour delay is estimated to cost an airline $600 per minute and data has shown that in 2019 delays cost airlines US$ 8.3 billion, making this a billion-dollar business issue.
Mobility and Connected Vehicles
A third area where cloud-edge computing infrastructures can benefit the aerospace industry is mobility infrastructure, advancing what’s possible for transportation networks and connected “smart” vehicles. Airlines are facing a number of challenges where the ability to use connected hardware to communicate as a knowledge engine could be beneficial. The same concept used to build a connected bike or autonomous vehicle could apply here. Airlines could use the edge to process crucial data close to its source and the cloud to support back-end analysis and to create a historical data repository.
This more emergent use case offers a number of possibilities for airlines: Could they better manage airport baggage logistics during transport from the plane to passenger pick-up? Could smart airplanes predict adverse travel conditions and automatically course correct during inclement weather? Could data collected “in the clouds” at the edge allow the aerospace industry and regulators to better track and optimize fuel consumption to manage global climate change commitments and green energy targets? Figuring out what’s possible will require advancing cloud and edge computing technology strategies.
Advancing Cloud-edge Use Cases Across Manufacturing, Maintenance, and Mobility
The aerospace industry, and aviation in particular, can potentially speed its adoption of cloud-edge technologies to advance these use cases by focusing on the following:
Map the data ecosystem across business and customer applications. Aviation companies can use this mapping to begin to think through data flows and what type of computing device / method (or combination) is best suited for the situation. As boundaries blur across mobile and sensing, edge, cloud, and continuously reporting sensing platforms, this mapping will be a critical to configure and manage cloud edge solutions.
Tap into the edge for applications and infrastructures that benefit from computing and AI close to the data’s original source. Intelligent edge solutions bring together the edge, AI, and advanced connectivity to compute, analyze, and run AI models close to where the data resides (at the edge) versus in a more distributed way (in the cloud). Determine which workloads benefit from this approach vs. a traditional Cloud ML approach, and partition accordingly. Whether data is in the cloud or at the edge, organizations will need to invest in security for data in flight, at rest, and during consumption.
Implement CloudOps and EdgeOps. Mobile, IoT, and other data will need clear operation and orchestration solutions to determine what gets computed where across the network. These solutions will need to balance human/machine, cost/risk, and data/technology orchestration across the computing ecosystem. CloudOps and EdgeOps will need to be considered together across people, processes, and tools.
Stay informed of continued computing and networking technology innovations. Technology is fast-moving and continuously advancing. Major telecommunications and cloud providers continue to introduce new solutions into the space. Keep a pulse on new solutions and services being provided by these organizations to advance new use cases with the latest technical capabilities and to learn from the latest implementations. Executives often experience a choice overload when evaluating multiple technologies. It’s important to assess how select innovations will help solve deep-rooted operational problems or create new avenues for revenue/margin improvement, along with long-term growth in an otherwise turbulent industry.
Edge computing is more expensive than cloud computing and organizations are not going to be able to hide the additional cost. However, one way it can be made profitable is by delivering end value to the customer that more than makes up for the premium. If organizations are taking what’s running in the cloud and just moving it into the edge, the cost of moving it is small, but the value you are giving the end user, the customer, is very little. This is why with edge-native applications, starting with the business problem is going to be crucial.