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The Value Question – What’s the ROI of Digital Twins in Manufacturing?
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The Value Question – What’s the ROI of Digital Twins in Manufacturing?

By April 24, 2024July 3rd, 2024No Comments

Table of Content:

Introduction
Quantifying Technology ROI is Extremely Difficult
The Impact of Digital Twins on Cost Optimization
Determining the Value of Digital Twins via Real-world Cases

Introduction

New technology adoption is now an established top priority for manufacturers. By 2029, the digital transformation market in manufacturing is expected to be worth $876.1 billion. The widespread use of technologies like the Internet of Things (IoT) and digital twins is transforming industrial processes like never before. Through real-time operations monitoring, these technologies enable preventative maintenance, reduce energy use, and boost overall productivity. While the benefits of these technologies are far-reaching and many, the value question plagues many. What is the true ROI of digital twins in manufacturing?

Quantifying Technology ROI is Extremely Difficult

While digital transformation progresses in the manufacturing sector. ROI is a key concern for CxOs. While most leaders understand the importance of embracing the latest technological innovations, demonstrating measurable outcomes doesn’t come easily.

  • The sheer complexity of technology tools and systems and extended implementation processes makes it difficult to quantify the impact on business outcomes.
  • The benefits of new technology adoption might not immediately reflect an increase in profits or revenue.
  • Many digital transformation initiatives generate intangible improvements in employee productivity, customer satisfaction, or brand reputation which can be tough to put in numbers.
  • Since technology projects often deal with other business processes, systems, and initiatives, these interdependencies make it challenging to determine the impact of a specific technology investment on overall business performance.

Without a compelling ROI, it becomes very difficult to garner funding and support for additional digital initiatives.

The Impact of Digital Twins on Cost Optimization

The modern manufacturer relies on a wide array of technology tools and systems to improve workforce productivity and safety, optimize production, and improve equipment performance and efficiency. From automation and IoT to artificial intelligence and augmented reality – it is estimated that the global smart manufacturing market will grow to $754.1 billion by 2030, exhibiting a CAGR of 13.5%.

While almost all these technologies play a huge role in fuelling better outcomes, taking a digital twin-led data-driven approach is emerging as a great way to optimize production and costs. As a comprehensive virtual model of any physical object, process, or service, digital twins enable data-driven decision-making and put an end to business-process inefficiencies.

By creating virtual representations of the physical world and its many relationships, they help optimize assets and streamline operations and maintenance. For asset-intensive

industries, digital twins can help benchmark asset performance, effectively manage SLAs, and increase yield and plant performance. In the long run, all these improvements can help boost production and optimize costs. Let’s understand how:

Manufacturing devices and equipment are highly susceptible to availability issues that can have extremely devastating consequences. From poor equipment maintenance to overuse, manual error, unexpected failure, cyberattack, etc. Even a few minutes of downtime can bring the entire production to a halt, while also causing losses in terms of idle workers, missed deadlines, reputational damage, customer dissatisfaction, and even penalties for late delivery. According to a recent survey, unscheduled downtime costs a staggering $125,000 per hour.

Creating a digital twin of production equipment can help manufacturers predict problems, get warnings, or detect anomalies in time and trigger actions based on pre-defined rules. Such intervention can help tackle the issue of downtime while maintaining asset performance and manufacturing efficiency. By mirroring the entire lifecycle of an asset, manufacturers can unearth powerful insights that improve overall efficiency and optimize maintenance activities.

Determining the Value of Digital Twins via Real-world Cases

The true value of digital twins is often reflected in terms of improved processes, reduced energy consumption, the reduced potential of equipment shutdown, and enhanced productivity. Let’s understand the ROI of digital twins via two real-world cases:

Case 1

A global discrete manufacturer was facing several issues in its production plants due to frequent mold changes, material unavailability, and maintenance issues. This resulted in unnecessary machine downtime, which reduced production efficiency and increased part rejection.

The implementation of IoT technology led to the creation of a digital twin of the injection molding plant. Sensors installed on each machine relay signals to PLCs to retrieve data from each injection cycle. Real-time data from different machines and molds, integrated into a large-capacity database, enabled alerts, dashboards, and reports that provide a clear picture of each machine’s current status and operational efficiency.

The amalgamation of IoT and the digital twin system resulted in several benefits for the manufacturer, including:

  • Improved machine utilization and planning efficiency.
  • Immediate action through alerts and shop floor dashboards.
  • Reduced rejection rates via cycle time analysis.

Case 2

A leading energy analytics company was struggling with the underperformance of its solar plants. Unknown breakdowns and efficiency woes led to poor decision-making for O&M and asset management teams while causing severe revenue losses due to delays in fault identification.

The implementation of a digital twin that is an electrical replica of the Solar PV plant led to real-time analysis of both historic and current behavior using sensors. Through effective data modeling and simulation, the energy company could enhance decision-making and drive higher cost efficiency.

Digital twin adoption helped the energy analytics company to:

  • Determine energy gain areas and increase plant performance by 5-7%.
  • Identify faults in real time and reduce the probability of breakdowns.
  • Conduct efficient advanced loss bucketing and performance benchmarking.

Digital twins play a huge role in enhancing the efficiency of manufacturing operations. However, the decision to invest in a digital twin system often brings with it the argument of ROI. What is the true value of digital twin implementation? How does it help in improving ROI?

A digital twin-led data-driven approach helps manufacturers optimize production and costs. By creating replicas of components, assets, processes, or systems, manufacturers can better understand behavior, detect issues, and make necessary performance improvements to improve device lifetime value.

Looking to implement digital twin at your manufacturing plant? Explore Pratiti Tech’s approach to digital twin software platform implementation and drive the ROI you expect and deserve!

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Nitin
Nitin Tappe

After successful stint in a corporate role, Nitin is back to what he enjoys most – conceptualizing new software solutions to solve business problems. Nitin is a postgraduate from IIT, Mumbai, India and in his 24 years of career, has played key roles in building a desktop as well as enterprise solutions right from idealization to launch which are adopted by many Fortune 500 companies. As a Founder member of Pratiti Technologies, he is committed to applying his management learning as well as the passion for building new solutions to realize your innovation with certainty.

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