In today’s world, virtually no industry is operating without consideration of their impact on the environment. It’s no secret that process manufacturers have been scrutinized for contributing to greenhouse gas emissions and excessive energy consumption, so striving for sustainability can sometimes be seen as a forced hassle. In contrast, however; achieving enhanced sustainability at a process manufacturing organization can actually result in better operational performance and efficiency, saving time and money for the manufacturer. Two birds, one stone.
In recent years, the UN created a set of seventeen Sustainable Development Goals (SDGs) to reach by 2030 in an effort to universally protect the planet. Of these are four that pertain particularly to process manufacturing companies and how they can contribute to the global effort:
These four goals have become a guideline for the industry as a whole to craft corporate sustainability goals, and it’s evident that these have become a top priority. Besides the obligations that require companies to invest in sustainable processes, it’s also become known that changing operations to better align with these goals results in many other positive impacts.
There are many challenges that process manufacturing teams face today in terms of meeting these sustainability goals. The first stems from the lack of tangible and actionable direction provided to team members at the plant, with broad guidelines set at a corporate level. Subject matter experts (SMEs) often do not have the resources within traditional data technology and methods to analyze their process data and make insight-based decisions to push their operation towards KPIs for improved sustainability.
The reality is that spreadsheets don’t provide any tools for efficiently contextualizing, cleansing, and analyzing data. Many teams spend numerous hours inside of spreadsheets trying to organize data for insight, leaving no time for actually making connections between the data that can lead to a reduction in waste, materials, or money spent.
Additionally, this method does not empower process manufacturers to make reliable predictions based on rapid and historical data. If an environmental violation happens, actions taken to correct it can only happen after it has occurred, and the opportunity to see what caused the problem can be missed.
With advanced analytics applications, process manufacturing operations can generate compliance reports automatically, with up-to-date data from disparate sources, freeing up time to focus on environmental impact.
Beyond monitoring of data as it’s happening and opening a world of insight during incident investigation, the accessibility, presentation, and correlation of data contributes to effective predictive analytics. This can give teams insight into when unproductive downtime may occur and lead to wasted resources.
Advanced analytics can also provide SMEs with a better understanding of how process changes will affect the environment by reporting on KPIs geared towards specific sustainability measures and creating models to compare process performance and operating conditions to ideal levels.
Beyond this, advanced analytics makes it easy to share insight across an entire team—leaving the days of spreadsheet-sharing in the past. Results are error-free and accessible for the whole organization to maintain the same mindset, so regardless of level, everyone knows the company’s progress towards improved sustainability.
Here are a few examples of ways that process manufacturers are utilizing advanced analytics to strive towards a better sustainability goals with lower impact on the environment, while also improving their operational performance.
The term “sustainability” can mean a lot of things, such as monitoring and controlling green house gas emissions, optimizing energy efficiency, implementing alternative energy sources, reducing waste and so on. These examples highlight the flexibility of Seeq; wherever you have environmental process data and would like to optimize your environmental performance, Seeq can be used.
SDG 6: Clean Water and Sanitation
Operations can avoid over-cleaning in clean-in-place (CIP) processes where sanitation materials can be unnecessarily used.
SDG 7: Affordable and Clean Energy
Process manufacturers are currently using advanced analytics to develop energy models and decrease total energy consumption, with minimal required capital expense.
SDG 12: Responsible Consumption and Production
Mass balance equations can be run continuously to track historical changes, providing an opportunity to find points where material is wasted.
SDG13: Climate Action
Many organizations are increasing generation of renewables and adopting smart grid technologies to mitigate carbon emissions through advanced analytics. Aggregation of methane emissions from various data sources through the use of advanced analytics can identify or predict places where methane is leaked, down to detailed micro-levels within the operation.
It’s simple: Investing in a sustainability goals strategy is good for business. The efficient use of raw materials, less waste, and lower energy consumption both directly lead to an improved environment and your bottom-line. In addition, sustainable practices such as these can boost your reputation above the competitors in your industry. See how advanced analytics can work for your operation today.
TQS Integration announces launch of their latest software release, ODIN, empowering the connectivity of real time data with cloud-based systems, machine learning and AI platforms in an easy, secure, and affordable way. This newly developed software enables TQS to help their customers achieve process manufacturing advances and propel towards industry 4.0.
Equipped with an easy to use, web-based interface, cloud data transfer through ODIN allows for real time and on-demand data egress to enable machine learning and supports multiple source and destination platforms. ODIN is compatible with both OSIsoft PI and Wonderware historians, allowing efficient and secure transfer of valuable information from multiple historians to cloud-based destinations including Amazon S3, Microsoft Azure Data Lake Gen 2, IOT Hubs, Event Hubs, SQL Server and more.
"We are very excited about what ODIN can do for our customers to provide an easy-to-use tool to solve the need for automated data extracts and remove the time-consuming process of extracting and contextualizing data. ODIN will allow that valuable time to be refocused back to data science and empower analytics and Industry 4.0.” says Emmett O’Connor, Global Head of Product Development at TQS."
The complex nature of cloud data transfer is now made easy as ODIN automatically aggregates, filters, contextualizes and delivers formatted real time information efficiently via a user-friendly GUI (Graphic User Interface) that enables ease of monitoring job success. In-built auditing and distributed agent’s nodes also ensure configurations are monitored for compliance, while transfers are seamless, secure, and scalable.
ODIN can help manufacturing companies to prepare compliance and regulatory reports, run predictive advanced analytics, integrate operations information with business information, ultimately gaining valuable insights to make optimized business decisions and cost savings. This tool allows TQS to deliver competitive advantage in digital transformation for their clients.
"ODIN enables companies to make key business decisions and operational improvements through the utilization of existing data – it brings Industry 4.0 and digital strategies to the next level. This further strengthens our position as the industry leader in data intelligence. TQS has seen significant expansion in recent years, more than doubling staff numbers over the past two years, and we are planning to add an additional 50 jobs in the next 12 months to support our continued growth" comments Korie Gleeson, COO at TQS.
About TQS Integration
TQS Integration is a global data intelligence company providing turnkey solutions in system architecture and application design, engineering, system integration, project management, commissioning and 24x7 “follow the sun” support services to valued customers. TQS is at the forefront of data intelligence for over 20 years, working with an extensive client base in the Pharmaceutical, Life Science, Food & Beverage, Energy and Renewables industries. As the go-to partner for data collection, cloud data transfer, contextualization, visualization, analytics, and managed services, we are the main drivers in the world’s leading companies — helping them become leaders in Industry 4.0.
For information, please contact us.
