Entering the era of software-defined manufacturing

The power of software-defined manufacturing

Today, product designs often have a shorter shelf life. Changing consumer tastes require flexibility in production. Manufacturing contends with thousands of variations as attributes adjust over the product life cycle. Software content is increasing in many products, with software-enabled features updated during the manufacturing process. Meanwhile, enterprises are struggling to manage decades of technology debt, process debt, and resistance to change—all which hinder the agility needed in smart manufacturing.

To manage these challenges while also driving transformational change demanded by industry 5.0, a new vision is necessary—software-defined manufacturing (SDM). In this vision, data, software, automation, products, and human workers are aligned to close the gaps in smart manufacturing systems. Manufacturing operations are controlled, managed, and optimized using software applications and services. At its fullest potential, SDM is the seamless orchestration of people and machines across software-defined factories, networks, and supply chains.

The challenge of change

Externally, manufacturers face mounting cost pressures and customer demands, with rising expectations for higher product quality, greater personalization, and lower costs. Internally, workforce constraints remain a challenge, with over 80% of manufacturers citing them as a reason for turning down business.¹

Meanwhile, legacy technologies on the factory floor lag behind innovation, limiting flexibility and agility across engineering and manufacturing. Even when systems are updated, the impact is often confined to a single factory rather than the entire network.

Determining the necessary enterprise changes to access software-defined manufacturing presents a challenge. Several key factors require attention:

• Siloed data and technologies inhibit connectivity and orchestration.
• Information technology (IT) and operational technology (OT) systems may be disparate and unintegrated.
• Cybersecurity risks become even more business critical as increasing data flows, devices, cloud services, and enabling hardware create attack vectors and vulnerabilities.
• Technology adoption both complicates and enables software/hardware abstraction.
  

A holistic approach is needed to align business strategy, technology investment, design and governance, and talent considerations. The goal is full ecosystem connectivity in a software-defined factory, where SDM environments, products, and interfaces provide visibility and traceability across engineering and smart manufacturing systems.

Taking the next steps toward SDM

SDM may take different shapes depending on the manufacturing sector and the nature of its production.

Investing in structured, integrated, and efficient frameworks accelerates digital transformation at scale to achieve strategic goals. Architecture and infrastructure, designed thoughtfully with an eye on process orchestration, empower users to build and leverage a broad set of high-value use cases, at scale, with a modern workforce.

In determining where to start and what comes next, smart manufacturers encounter key questions in the areas of data management, governance, and the workforce experience.

Data management considerations
How do we prepare data for AI and scalable solutions?
How do we analyze the data?
How do we deliver insights to people—or systems—at the right time?

Technology governance considerations
How do we do this securely?
How do we apply this at different levels of scale across operations?
How do we transform the software development life cycle?

Workforce considerations
How does SDM enhance the workforce experience?
How do we roll out and sustain new ways of working?

Taking the next steps on the path to SDM

There are two overarching aspects to software-defined manufacturing transformation.  First, a continued focus on engineering principles to create flexible products that adapt over time to customer demands and new technology.

Second, a recognition that automation and factory tooling require high up-front costs for hardware, but that as SDM’s efficiency and productivity gains take effect, these initial costs give way to savings and revenue.

SDM requires executive sponsorship and change leaders across functions. By aligning decisions and investments with enterprise strategy, executives can drive change and engage organization-wide stakeholders to leverage smart manufacturing.

Technology innovation is moving fast. Modernize opportunistically with investments in foundational capabilities and process transformation. Take a holistic view of technologies that drive incremental, high-frequency use cases with lower costs and effort. Design for connected data and integrated systems within software-defined factories, across the network, and throughout the supply chain.

Finally, leaders should approach SDM with the human workforce in mind as they move towards the future of manufacturing. New technologies require new skills but should build on existing knowledge.
 

Acknowledgments

The authors would like to thank subject-matter specialists
Jason Bergstrom; Lindsey Berckman; Stavros Stefanis; Rohini Prasad; Alex
Bredemus; Leslie Koff; Chris Culver; Chris Como; Jon Tidd and Zachary Drew of
Deloitte Consulting LLP, and Jason Hunt and Anne Robbins of Deloitte & Touche
LLP who played an instrumental role in the development and publication of this
business paper. Your invaluable insights and contributions have significantly
enriched the quality and depth of this work.

End notes

¹Deloitte & The Manufacturing Institute Perception Study, 2021

²“What Are Industry Cloud Platforms?,” Gartner.com, November 16, 2023.