I cover industry solutions for manufacturing and a few other industrial markets at AWS. My goal isn’t to work with customers on a specific technology, but rather on how customers can use technology to address business challenges. This role gives me an opportunity to work with global leaders on how innovation can deliver new levels of competitive differentiation.
As you might expect, IoT, Industry 4.0, and digital manufacturing are top of mind for manufacturers globally. One challenge common to all of these trends is how to use production data to drive business operations. On this, most manufacturers don’t know where to start. Despite all the noise in the market, for the most part, manufacturers are in paralysis mode.
So what’s driving this inability to execute or scale pilot initiatives? I’ve found that for the most part, manufacturers are starting with the wrong focus.
Here’s what I mean.
When beginning IoT and digital initiatives, most manufacturers, analysts, and consultants, speak about adding sensors to capture new sources of data to see what is happening in operations. Initiatives will often be based on deploying smart sensors or new ways of tracking materials or WIP.
But this approach has a number of challenges: deploying connectivity to older machines can be expensive, and moving data from remote locations can be difficult.
More importantly, manufacturers often don’t have the technical or organizational infrastructure in place to take advantage of this new level of insight. More data creates a bigger black hole of unused data. They are missing ways to turn this raw new data into something that enables them to make better decisions. They don’t have the operational processes or change management resources in place to react differently. All of this speaks to the issue of IT vs Operational Technology (OT) misalign. I’ve seen too many examples of how failure to bring the best practices and needs from both of these groups ends up limiting transformation business impact of projects.
A Better Approach
So what’s a better approach? Manufacturers should start by working with the data they have, and use this to build the technology platform and operational capabilities necessary for change. There is a huge mass of data in manufacturing environments, and most is never looked at. It’s not about getting more data, it’s about making the data you have useful. Manufacturers who do this are able to unleash a whole new set of capabilities. Once you start to understand the data you have, you can look at how to fill in potential gaps with additional sensors or data sources.
When we work with manufacturers, one of our key goals is to help them review the data they have and uncover addressable use cases today. Only then can they identify projects with short-term impact.
Many of the manufacturers we work with have data in historians, operational data stores, or distributed systems across their network of plants. The key is getting that data into a place where it can be utilized, solving the issues around data aggregation, transformation, and accessibility first, then add that advanced analytics. Cloud brings low costs to data aggregation, transformation, and compute enabling manufacturers to gain insight from current data generating assets.
Unleashing a Whole New Set of Capabilities
Building a centralized cloud environment for production data from across the enterprise creates a platform that manufacturers can use to deliver capabilities today. By working with existing data, manufacturers can start to build out operational capabilities needed to ensure future projects are successful while lowering costs and improving operational KPIs.
With cloud capabilities manufacturers now have the ability to work with terabytes or petabytes of data aggregated from multiple sources. This takes a lot of memory and processing power that was previously not economically feasible for manufacturers to deploy in their facilities.
Beyond the cost benefits, centralizing data also provides a new way for manufacturers to manage production. Traditionally, cross-facility production benchmarking and monitoring had been based on backward looking reporting. With a centralized platform of real-time or near real-time production data, manufacturers can now compare site A vs site B, to deliver new levels of insight for capacity planning, production management, and supply chain.
A centralized cloud platform doesn’t mean that manufacturers can’t take advantage of low-latency applications. With technologies like AWS IoT Greengrass, manufacturers can build algorithms in the cloud where they have enough data volume to validate the analytics and then deploy them locally as needed. It’s far more cost effective to innovate manufacturing analytic solutions in the cloud and then deploy them locally.
Building out a data platform for innovation is critical to ensuring manufacturing IoT initiatives can be successful long-term. Once production data from across multiple locations is aggregated, manufacturers can begin to build out the capabilities which will transform the data into a resource for improving business.
In the past, manufacturers had moved their data to the cloud, facing a great deal of development work necessary to integrate quality, process, and raw material data into something useful for managing the business. Today, built-for-the-cloud platforms like Sight Machine, enable manufacturers to quickly transform and contextualize this data into a single, integrated source of truth. This cloud-architected data platform can then quickly be enhanced with other AWS services.
Once this digital infrastructure and operational capability are in place, manufacturers can evaluate new projects, with new sensors, and new capabilities. Visit this page to learn more about AWS manufacturing solutions. Visit our use case page to see examples of how AWS can partner with Sight Machine to deliver business from production data.