Improving Sustainability in Manufacturing with Digital Twins

Introduction

Sustainability has become a cornerstone in the manufacturing industry. As stakeholders increasingly prioritize sustainability, the sector is turning to technological innovations to meet these demands. Among these technological advancements, the concept of Digital Twins stands out as particularly transformative for the manufacturing industry aiming for sustainability.

Though manufacturing encompasses a wide range of topics, this article will specifically concentrate on manufacturing within the Consumer Packaged Goods (CPG) sector. For CPG companies, Digital Twins can serve as dynamic virtual replicas of manufacturing processes, product lines, packaging systems, or even comprehensive supply chains. By integrating real-world data from sources like Internet of Things sensors, machine metrics, and historical performance records, these models allow for meticulous monitoring, simulation, and optimization of performance. By moving the prototyping, testing and optimization phases of the product lifecycle to a virtual environment, organizations significantly reduce not only the material needed to create multiple iterations of prototypes, but also the demand for materials and the amount of byproducts they need to develop products and processes now and in the future. For more information on classification of Digital Twins and its various maturity levels, refer to Digital Twins on AWS: Unlocking business value and outcomes.

In this article, we delve into the critical sustainability KPIs that manufacturing organizations prioritize and explore how Digital Twins can significantly transform their measurement. We’ll spotlight a case study of a global CPG brand that has adeptly harnessed Digital Twins technology to quantify Energy & Water savings. Most importantly, you will learn about the various AWS services that help implement a Digital Twin within your manufacturing setup, and in turn, support your sustainability goals by reducing your overall carbon footprint by as much as 20 percent.

Digital Twins driving Sustainability Goals

Digital Twins play a significant role in sustainability efforts by helping organizations quantify the performance of physical systems and reduce their environmental impact. A notable application in the virtual realm is in simulating new product designs, packaging alternatives or manufacturing configurations to reduce energy consumption, water consumption and waste. This pre-emptive modeling enables identification of sustainability enhancements, ensuring these are embedded even before actual implementation, some of which are listed below:

1. Energy Efficiency: Manufacturing companies can harness Digital Twins to fine-tune energy consumption patterns, leading to significant reductions in greenhouse gas emissions from Scope 1, Scope 2 and Scope 3 emissions. A recent report from professional services company EY found that digital twins can help to reduce the greenhouse gas emissions and carbon footprint of an existing building by up to 50 per cent, alongside cost savings of up to 35 per cent.
2. Waste Management:  Digital twins can virtually help to look beyond the current industrial model of extract, produce, consume, and dispose. Thus, companies and even entire cities have options to shift to a “circular economy” system that considers almost zero production of waste and pollution, keeps products and materials longer within the recycling loop, and helps to regenerate natural systems.
3. Sustainable Design: Digital Twins offer real-time tracking of carbon footprint across the entire supply chain and calculate product design and development life-cycle carbon footprint, ensuring a transparent and sustainable design-to-delivery journey. This article on strategies to lead product sustainability design gives you more information on this strategy. By utilizing conventional design technologies, companies can reduce a product’s environmental impact by up to 40%.
4. Logistics Emissions Reduction: Digital Twins assist in optimizing logistics and distribution, curtailing logistics related carbon emissions. In Logistics, the Digital Twins technology can drive revenue increases of up to 10% and improve product quality by up to 25%.
5. Water Conservation: Digital Twins can be pivotal in manufacturing sector that demands significant water usage, ensuring optimal water conservation strategies.
6. Strategic Planning: Manufacturing companies can leverage Digital Twins for predictive insights, guiding resource allocation and investment strategies for sustainable growth.
7. Stakeholder Engagement: Communicating sustainability measures to stakeholders becomes streamlined with Digital Twins by offering visual and quantifiable representations of sustainability related strategies.

Architecture Overview

Below, we’ve outlined a reference architecture designed for implementation in factories and tailored to monitor your sustainability objectives. This architecture was deployed in a customer’s bottling plant which produces carbonated drinks, water, and a variety of fruit juices.  The key AWS services used in this reference architecture are AWS IoT SiteWise, a managed service that makes it easy to collect, store, organize, and monitor data from industrial equipment at scale and AWS IoT SiteWise Edge, a service installed on local hardware or AWS devices which streamlines on-premises data collection and organization. A combination of these services offers factory operators insights into equipment data to enhance uptime, product quality, and efficiency, all while maintaining functionality during intermittent cloud connectivity.

Additionally this solution also uses AWS Services such as Amazon S3, AWS Lambda, Amazon DynamoDB, Amazon Kinesis Data Firehose, AWS Glue, Amazon Athena, and Amazon Managed Service for Grafana.

The implementation took 4 weeks as the core IoT components, templates, asset models and metric collections required for data collection are included with AWS IoT SiteWise.

In this implementation, AWS IoT SiteWise Edge is installed on premises, which collects IoT data from the PLCs through an OPC/UA server such as KepserverEX. The data is sent to the cloud where its further enriched using business rules and process-related information using AWS IoT SiteWise. For calculating the Metrics and Data storage, a combination of AWS Lambda, Amazon DynamoDB, Amazon S3, AWS Glue, and AWS Kinesis Data Firehose are used. For presenting the data for consumption, near real-time visualization, and further analysis Amazon Athena and Amazon Managed Grafana  dashboards are used.

Building upon this initial architecture, we can achieve comprehensive command, control, and visualization capabilities by integrating additional AWS services, like AWS IoT TwinMaker. AWS IoT TwinMaker allows developers to create digital twins of real-world systems, streamlining building operations, enhancing production, and improving equipment performance using existing data and 3D models for a comprehensive operational view.

How to calculate Sustainability KPI Metrics

By utilizing the Digital Twin Implementation framework explained above, a factory is equipped to capture various sustainability KPIs that might be required for compliance and reporting purposes in order to be certified for sustainable operations. For this CPG customer, the initial proof of concept focused on Energy Efficiency and Energy Savings. This was later expanded to encompass Water Conservation and Waste Management.

The implementation of the Digital Twin solution includes a step-by-step approach to calculate current energy usage and potential savings. First, a comprehensive energy audit captures the plant’s energy consumption. We use AWS IoT SiteWise Edge to relay this data to AWS IoT SiteWise. This audit data aids in capturing the overall energy use and the primary energy-consuming equipment. The energy consumption is further categorized by department or process and energy type. Following this, energy efficiency metrics are calculated typically representing the output-to-energy input ratio. This sets the stage for identifying areas needing improvements, from updating existing equipment to addressing operational inefficiencies.

How to quantify Energy and Water Savings

Key strategies used to enhance sustainability include transitioning to water-efficient equipment, promoting water recycling, reducing and eliminating waste, fostering staff training on sustainable practices and last but not the least deploying predictive maintenance solutions to predict equipment failure and avoid down time. Upon enacting the conservation measures, it’s vital to assess the achieved versus targeted KPIs, translating these gains into monetary terms using prevailing water costs and waste management expenses. This not only quantifies the benefits but ensures long-term commitment to sustainable measures. Regularly evaluating these KPIs ensures ongoing improvement, at the same time, external validations and certifications can affirm and amplify a plant’s dedication to eco-friendly operations.

Once these tracking and monitoring measures are in place, organizations can quantify their energy and water consumption savings by comparing post implementation consumption to the baseline. These energy, waste management and water savings can be translated into monetary terms using current market pricing. Integral to the long-term success of these endeavors is the adoption of continual monitoring of these systems combined with periodic audits.

How to add Sustainability KPI Metrics

Adding a new sustainability KPI metric is relatively simple as a Digital Twin establishes a baseline for capturing additional metrics. For example, when a manufacturing plant wants to add water conservation metrics or waste reduction metrics, above documented process is repeated. For example, initial audit captures baseline metrics on water consumption and waste generation, and subsequently identifying predominant water-intensive and waste-contributing processes step is performed and potential areas for improvement are identified. By segmenting water usage as per origin, such as specific departments or processes and categorizing waste based on its type and origin, manufacturing plants can effectively set sustainability KPIs to monitor inefficiencies.

Scaling Digital Twins with additional capabilities

As organizations continue to evolve their basic Digital Twin implementations with additional capabilities and functions, they can leverage several AWS services, say for example, Amazon Lookout for Equipment, which is an AWS service that leverages the sensor data for factory equipment, collected by AWS IoT SiteWise for predictive maintenance and anomaly. AWS IoT TwinMaker is another AWS service that enhances the Digital Twin capabilities by creating 3D replicas of all your manufacturing assets, buildings, plants and HVAC systems with command-and-control capabilities. In summary, it creates a holistic view of your entire operations in a single virtual system.

Conclusion

In this article, we delved into a Digital Twin implementation that can be deployed on AWS. Additionally, we highlighted the key performance indicators (KPIs) to track, ensuring you’re on the right path towards achieving your sustainability objectives. By constructing virtual replicas of your manufacturing systems, production lines, and even products, Digital Twins can facilitate near real-time surveillance and monitoring of your sustainability KPIs such as water, energy consumption, and waste management. Armed with these insights garnered from Digital Twins, organizations can further optimize resource utilization, lower carbon footprint, and align their strategies towards more sustainable production and distribution. Embracing the capabilities of Digital Twins in the CPG landscape allows you to make measurable progress towards building a sustainable and resilient ecosystem for future generations. If you would like to seek more information on how AWS is supporting other customers with their Digital Twin implementations and sustainability goals, please review the following resources:

1. Building Efficient Digital Twins in the Construction Industry
2. Digital twins and CPG manufacturing transformation
3. How to make digital technologies for the circular economy work for your business
4. Accelerating the shift towards a sustainable economy using HPC on AWS

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