Honeywell’s Journey to Autonomous Operations

Here are three things every industrial company should know before embarking on a path toward industrial autonomy.

Torsten Pilz, SVP and Chief Supply Chain Officer

January 5, 2024

4 Min Read
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lorenzo rossi via Alamy Stock

The industrial sector is embarking on a new era of fully autonomous operations in which machines, equipment, and systems can perform their tasks and make decisions without human intervention. At Honeywell, we know this new era is coming because we are well down the path of making our internal operations fully autonomous. 

What does autonomy look like? Consider the scenario where an organization is tasked with making a thousand decisions each day. Now imagine being able to leverage AI to automate approximately 900 of those decisions. This allows organizations to concentrate on the remaining 100 critical decisions that either machines cannot handle or we, as humans, prefer to make ourselves. 

AI-powered Automation 

In the past, a large industrial company needed thousands, or even tens of thousands, of people focused on basic decision-making and executing relatively simple, yet time-consuming, tasks. Now, these kinds of tasks can be achieved through an AI-powered automated system that can optimize processes, troubleshoot issues, and make adjustments with limited human oversight. 

But automating operations and decision-making is easier said than done. There is no single product or system in the market that a company can buy to achieve fully automated operations. That’s why we set out to build such a product for its own internal operations. 

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Autonomy in Action

For instance, we’ve implemented AI co-pilots for our customer-service team, significantly accelerating their work by 30-40%. These co-pilots sit next to team members, analyzing massive amounts of data and guiding them in terms of what problems to focus on and how to go about solving them.

Our technical service teams have undergone a similar transformation. We’ve integrated AI into our technical-support operations, enabling customers to receive answers to their technical questions within minutes or seconds, as opposed to the day or two it previously took. 

Today, the addition of generative AI has amplified the capabilities of industrial AI, making it even more powerful than ever before. For example, we’re currently looking at millions of instances of alarms being triggered in the plants of our industrial customers -- to evaluate the potential use of such historical datasets to train a robust language model that would assist plant operators in identifying and addressing alarm issues promptly and providing guidance on necessary actions. 

Productivity is always about doing more with less. It’s also about growth and enabling people to work more effectively and efficiently by automating certain tasks -- and without having to worry about a skills shortfall in a tight labor market.

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Getting Started

Here are three things that every industrial company should know when embarking on their own autonomy journey:

1. Automated decision-making is available now (not five years from now)

For the last 25 years, people have been talking about automated operations. Today, it is finally a reality. The combination of massive computing power, advanced AI algorithms and next-gen sensor technologies means that industrial systems can now process vast amounts of data at lightning speeds. These systems can analyze historical data and predict potential issues in real time. 

Recently, for instance, during the tail end of the semiconductor shortage, certain areas of our business experienced a significant backlog. In response, we developed an AI-based model trained on extensive datasets. This model played a crucial role in identifying solutions, such as determining which orders to prioritize, figuring out the best ways to route materials through the system, and assessing the reliability of suppliers. 

2. Data connectivity is key

Large industrial organizations, including ours, used to spend up to 60% of their IT investment budget on trying to connect disparate enterprise systems -- ERP systems, logistics systems, transport management systems, etc. By leveraging a new unified data infrastructure, organizations can automate their decision-making processes -- accomplishing exponentially more without increasing the IT budget.

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In our case, we created a repository of data assets where everything that happens in our operations is stored.  At any given moment, I know what our inventory looks like for any given SKU across the entire universe of Honeywell. We now have dozens of these consoles -- a logistics console, a maintenance console, etc. -- giving us total visibility into what’s going on. 

3. You need the right partner to be successful

With the convergence of IoT and AI software, the journey to autonomous operations is accelerating rapidly in the industrial world. However, automated decision-making requires both domain knowledge and the technical capabilities to build such a system. In vetting potential partners, look for one with the experience, data, and domain expertise to help you make the transition at scale.

Automation and AI are undoubtedly the keys to remaining competitive in an increasingly complex operational world. In the end, the companies that truly commit to making transformative changes toward autonomy will ultimately become more sustainable, resilient, and agile businesses positioned for long-term success.  

About the Author(s)

Torsten Pilz

SVP and Chief Supply Chain Officer, Honeywell

Torsten Pilz oversees Honeywell’s global integrated supply chain, with responsibility for driving improvements in plant efficiency, working capital, quality and delivery.

Before joining Honeywell, Torsten was Vice President, Supply Chain, for SpaceX, where he was responsible for planning, purchasing, material management and logistics. His team supported dozens of launches a year, as well as the development and production of the Falcon and Falcon Heavy Rockets, the Dragon Spacecraft and SpaceX’ satellite program.

Torsten earned B.S. and M.S. degrees, as well as a doctorate in chemical engineering, from the Karlsruhe Institute of Technology in Germany.

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