Purdue’s ManuFuture Today Initiative drives digital transformation for small manufacturers

A group of students working at Kirby Risk Precision Machining in Lafayette, IN
A group of students working at Kirby Risk Precision Machining in Lafayette, IN

A Purdue University initiative is tackling a critical economic challenge: helping small and midsize manufacturers adopt digital technologies to improve efficiency and remain competitive. The innovative engagement model, ManuFuture Today, developed with support from the National Science Foundation (NSF), has shown promising results, including one success story where a participating company more than doubled its productivity within a year.

ManuFuture Today addresses a long-standing issue for small and midsize manufacturers, which make up 98.6% of all U.S. manufacturing firms and employ nearly half of the industry’s workforce. Despite their importance, these firms often lack the resources—time, funding, and expertise—to leverage the transformative potential of digital technologies.

Ali Shakouri, a professor in Purdue’s Elmore Family School of Electrical and Computer Engineering and Associate Dean for Research and Innovation for the university’s College of Engineering, is leading the effort.

“ManuFuture Today is not just about isolated success stories,” said Shakouri. “It’s about establishing a replicable engagement model that empowers small manufacturers to navigate their digital transformation through collaboration and peer learning.”

The ManuFuture Today methodology centers on forming learning and innovation networks—cohorts of manufacturers focused on specific challenges—guided by Purdue researchers and industry experts. Manufacturers meet regularly with researchers. Every six months, stakeholders convene to share progress, exchange knowledge, and explore new strategies for overcoming barriers to technology adoption.

The challenges of small and medium manufacturers seem far from cutting-edge research in universities and big companies pushing the limits of artificial intelligence and new manufacturing processes. Researchers from several schools in the Colleges of Engineering, Science, and Polytechnic at Purdue, in collaboration with partners at Harvard, Tuskegee University, and Ivy Tech Community College, have identified important research opportunities in developing privacy-preserving artificial intelligence data communities1 as well as reliable sensing with low-cost internet-of-thing and tiny machine learning devices.

Rather than imposing top-down solutions, the program emphasizes helping manufacturers design their own digital journeys. Technological innovation must be coupled with organizational culture and business operation changes where front-line workers take ownership. Manufacturing cohorts take the lead in implementing and customizing solutions, engaging their workers and fostering sustainable innovation.

“We don’t simply hand them Purdue technology and expect magic to happen,” Brad Beach, Managing Director for ManuFuture, said. “We engage them in a process of learning by doing, and along the way they learn how to evaluate the impact of sensors and data, how to think about and apply AI models, how to integrate commercial solutions, how to apply their own in-house innovations, and most importantly, how to add real value to their business.”

One standout success involves Kirby Risk Precision Machining (KRPM), a supplier to industries including agriculture, oil and gas, and power generation. KRPM faced inefficiencies stemming from limited visibility into shop floor operations and reliance on manual production reports.

Through its involvement in ManuFuture Today, KRPM collaborated with Purdue researchers to deploy low-cost sensors, data analytics, and intuitive dashboards. The initial results were very encouraging. Subsequently, KRPM identified a commercial vendor to connect all of their tools digitally. As data and information flow were overwhelming, they developed a custom communication flow and data interface with open-source tools with the help of a Purdue intern. The results were transformational: in just one year, KRPM doubled its productivity.

“Before this transformation, communication relied on handwritten notes and in-person conversations,” said KRPM Continuous Improvement Manager Dave Roberts. “Operators would walk an average of 62 miles annually to locate supervisors, costing 370 hours of productivity.”

With the new system, operators now use tablet-based dashboards to monitor machine performance and request support instantly. These innovations eliminated inefficiencies and streamlined workflows.

Beyond internal improvements, KRPM has become a role model for other manufacturers in the cohort, sharing its journey and lessons learned to inspire broader adoption of digital solutions.

ManuFuture stakeholder meeting on Dec. 9, 2024 on the West Lafayette, IN, campus of Purdue University

ManuFuture stakeholder meeting on Dec. 9, 2024 on the West Lafayette, IN, campus of Purdue University

In another example, Primient, a food processing company in Lafayette, has been working with Purdue and Harvard to implement a simple machine learning imaging application to help its operators evaluate its production process for the size distribution of sugar crystals2. The new application provides measurement precision to a process previously prone to human error and wide variability. The tool has been used daily for over a year by more than 30 operators.

The ManuFuture Today initiative has drawn national and regional attention, which was highlighted in an article in Harvard Business Review. Several dozen manufacturers in Indiana and Northeast Ohio currently participate in the multiple learning and innovation cohorts. The program’s success highlights the potential of combining artificial intelligence with peer learning to accelerate digital transformation.

“We’ve proven this engagement model works at a regional level, but the challenge now is scaling it nationally,” Shakouri said. Purdue is now working with regional, state and national partners to expand ManuFuture Today’s reach.

As the manufacturing industry faces growing pressure to modernize, ManuFuture Today offers a scalable and sustainable solution to help small and midsize manufacturers adapt and help create a more resilient US manufacturing ecosystem. By fostering collaboration, building trust, and focusing on achievable outcomes, the initiative is driving real change and strengthening the backbone of the U.S. economy.

“Small wins lead to big transformations,” Beach said. “ManuFuture Today is proving that, with the right support, even the smallest manufacturers can achieve extraordinary results.”

1Beyrle Barker L, Shank J, Sweeney L. “Trustworthy AI Data Communities (AI-DCs): Unlocking the benefits of AI for all, using U.S. manufacturing as a case study.” Accepted for publication in the Journal of Technology Science, Jan. 2025

2Ji X, Shorland J, Shank J, Delpe-Brice P, Sweeney L, Allebach J, Shakouri A. “Empowering Manufacturers with Privacy-Preserving AI Tools: A Case Study in Automating Quality Control Through Machine Learning.” Submitted to publication in ACM Queue, Dec. 2024

The Business Case for Digital Transformation: The Shop Floor Perspective

Tim Stuart from Visual Decisions, looked at the same question — creating value frm digital transformation — from the perspective of the shop floor. Some of his key points: 

  • Is there one department that is driving digital transformation? There are many different places to start the digital transformation journey. 
  • Are you doing a digital transformation of the enterprise or a digital solution to an immediate problem? Think about:
    • Value and time-to-value
    • Use case selection: there are hundreds of places to start. Am I focused on a narrow focus or am I designing a digtal transformation for the business
  • Resources: What are the time constraints? Can I bring in external resources? 
  • Readiness: Is my network ready? Do I have cybersecurity in place? Do people on the shop floor have the skills and behavior flexibility? 
  • Impact on production: How disruptive will your digital initiative be?
  • Focus on ease of implementation. Don’t start with an initiative that requires a huge effort. Focus on small initiatives that can scale. 

You will not get the performance you want unless you also focus on the changing skills, behaviors, and routines needed to suppoort the digital change. 

“Just buying a FitBit will not make you lose weight.” 

You can get access to Tim’s video and slides by joining our open community: ManuFuture Today: Leveraging AI for Small and Mid-Sized Manufacturers.

Just click here to join.

The Business Case for Digital Transformation: The CEO Perspective

On December 14, we conducted the next in our series of workshops to accelerate the digital transformation of manufacturing. We explored two different dimensions. The first is the CEO perspective. How do you present digital transformation to the C-Suite?

Mike King of LHP Analytics presented some useful frameworks to make the case. Some key points:

  • Provide a visual framework and continuously focus on key questions: It’s easy to get lost.
  • Two primary objectives for digital transformation: Where is your focus?
    •  Solve problems
    • Drive improvements
  • Figure out where you are on a digital maturty level: Where are we? It’s all part of establishing your baseline. 
  • Five key questions from the C-Suite perspective:
    •  What is the problem?
    • What caused the problem?
    • What are we doing to fix the problem?
    • When do we recover? 
    • How does this impact earnings? 
    • What help do you need to answert these questions?
  •  Once you have this framework in place, answer the question: “How will digital help”?

For more on Mike’s presentation, including his slides and a video of his presentation, join our ManuFuture Today learning community: Leveraging AI for Small and Mid-sized Manufacturers. It’s free. Click here to join. 

Research: Profiting From Data Commons

ManuFuturew Today is exploring how we might generate and share data among smaller manufacturers, in order to speed their digital transformation. Large companies have an internal infrastructure to capture and analyze data. Smaller manufacturers don’t. How can we pool data among smaller manufacturers to that we can speed their journey.

Recently Ali Shacouri sat down with a leading MIT researcher, Eric von Hippel, to explore these issues.

What is a “data commons”? How can it accelerate innovation? These topics and others are covered in a new scholarly paper: “Profiting from Data Commons: Theory, Evidence, and Strategy Implications”. We have posted the paper in our community.

You can read the Abstract here:

“We define data commons as repositories of freely accessible, “open source” innovation-related data, information, and knowledge. Data commons are and can be a significant resource for both innovating and innovation-adopting firms and individuals. First, the availability of free data and information from such commons reduces the innovation-specific private or open investment required to access the data and make the next innovative advance. Second, the fact that the data are freely accessible lowers transaction costs substantially. In this paper, we draw on the theory and empirical evidence regarding innovation commons in general and data commons in particular. Based on these foundations, we consider strategic decisions in the private and public domain: how can individuals, firms, and societies profit from data commons? We first discuss the varying nature of and contents of data commons, their functioning, and the value they provide to private innovators and to social welfare. We next explore the several types of data commons extant today and their mechanisms of action. We find that those who develop innovation-related information at private cost already have, surprisingly often, an economic incentive to freely reveal their information to a data commons. However, we also find and discuss important exceptions. We conclude with suggestions regarding needed innovation research, data commons “engineering”, and innovation policymaking that could together increase private and social welfare via enhancement of data commons.”