Digital Transformation in Manufacturing

Digital transformation is an elusive target. I’m fond of saying that, like great art, I can’t tell you what it is but I know it when I see it. That’s certainly the case when it comes to digital transformation in manufacturing. It is difficult to have and hold a clear vision, but it’s also quite challenging to implement as you realize the impact it will have on your processes and systems. 

Change is hard. And even the people you’re trying to help need guidance through the digital transformation process.

Manufacturing: An Industry of Transformation

The manufacturing industry is no stranger to transformation. Over the last 50 years, it drove the evolution of several technologies and industries, including robotics, automation, and statistical process control. It drove standards such as SECS/GEM for machine data exchange and Good Manufacturing Practices (GMP). The rapid expansion of IoT- connected sensors provided telemetry to measure the quality of inputs and the health of equipment used in the manufacturing process. 

Manufacturing also inspired massive investments in machine vision, image processing, AI and machine learning, and powerful software applications. These applications include Warehouse Management (WMS) and Manufacturing Execution Systems (MES), Document Control, and Recipe Management systems designed to realize complex requirements driven by ISO-based Quality Management Systems (QMS). 

Lean Manufacturing drove the integration of manufacturers’ forecasts to upstream suppliers towards Just In Time (JIT) to reduce inventory levels and shorten manufacturing lead times. Software systems have been integral to these leaps forward in productivity and quality. Surely it’s time to thank the industry for a job well done and let it take a much-deserved break from unrelenting transformation.

What’s that? No rest for the weary? The search for increased productivity and yields never ends. Innovation in Cloud and AI/ML technologies and services creates new opportunities. And macro trends like shifting demographics, labor costs, competition, governmental policies, and environmental concerns all change the demand for manufactured goods in unpredictable ways and reveal new reasons to seek new efficiencies. 

Let’s look at a few more specific examples of digital transformation in manufacturing that we’ve encountered with our clients.

Digital Transformation in Manufacturing: Adapting to Uncontrollable Inputs and Environments

Industries such as semiconductor manufacturing have accomplished remarkable improvements in yield through closely-monitored environmental controls. Other industries, such as concrete manufacturing, don’t have that luxury. 

Concrete often has rather tight tolerances to hit regarding the strength and dimensional slump of the resulting shape. It also has a remarkable variation in ingredient temperature, humidity, water content, alkalinity, and additives. It’s impractical to eliminate all of these variables to improve yields. Lastly, it takes days to weeks to mix and test a small batch of concrete to determine if it will meet your specifications. By the time you have the answers, the conditions have changed, and your lead times have extended.

Instead, imagine that you have a mobile application that provides real-time sensor information and product specifications right there in the yard. You can pull up the order specs and run a machine-learning-based prediction model for how to achieve the desired result using a variety of additives to compensate for material and environmental conditions. This is all possible with current technologies and services that will have a tangible impact on the quality and yields in concrete manufacturing. This is what I would call digital transformation in manufacturing.

Digital Transformation in Manufacturing: Environmental Impact and Governmental Policy

Science has established the link between carbon emissions and climate change. But our industries are just beginning to figure out how to adapt existing or create new technologies to address these changes. In some cases (electric vehicles, even power generation, etc.), widespread changes are being made to manufacturing and delivering these systems to improve efficiency or reduce emissions.

We tend to think of heavy industry and transportation first, but the agricultural sector is also innovating in various ways. All of this innovation is linked to carbon credit exchanges that allow farmers to participate. In addition to reducing emissions, they can also generate carbon credits by sequestering carbon through regenerative practices such as cover crops and conservation tillage. 

Carbon offset trading represents another form of digital transformation driven by carbon emissions policies driving innovation.

Digital Transformation in Manufacturing: Reactive and Preventative Maintenance

We’ve already discussed how smart sensors used within the manufacturing process and equipment can directly impact yields. But what about improving yields and uptime by determining if the equipment is beginning to fail before it happens? 

A couple of years ago, Amazon Web Services (AWS) launched a completely packaged and managed service called Monitron. It provides all the sensors, network appliances, and cloud services needed to roll out your own predictive maintenance program. 

Manufacturing equipment generates vibration and heat as it operates. During a relatively short training time, the machine learning models provided with the service learn the characteristics of the equipment. After some training, these models are ready to notify your team if the patterns change, indicating that the machines may need maintenance.

We’ve built a wide variety of mobile applications that extend equipment sold for various purposes, including automatic steering, paint spraying, and floor polishing, among many others. In each case, manufacturers expanded their reach to make their devices smarter and allow them to monitor and predict correct operation.

More Than Manufacturing

Of all the challenges manufacturers face, the most daunting is the rising importance of digital technologies and services tied to both how and what they manufacture. In virtually every industry, from concrete to cows, digital applications and machine learning provide visibility and insight into massive amounts of data collected as we build these products or while they are in use in the field.

This presents a new challenge for these manufacturers. 

How do they transform their product design, manufacturing culture, and processes to also deliver innovative and engaging consumer and industrial experiences? How do they build and blend the Agile culture with their existing product life cycles to become a provider of successful software and services without losing their core design and manufacturing capabilities? 

The best approach is to graft the needed skills and mindset into your organization’s DNA by choosing a partner that understands why this is hard and can show you how it is done.

Photo by Mech Mind on Unsplash