Digital Solutions Drive Plant Agility: Thriving in an Uncertain Economy
Enabling agility and resilience through digital manufacturing will allow your company to survive and thrive in today’s tumultuous economic times, writes Sree Hameed, Consumer Products Industry Strategist, AVEVA.
For centuries, the manufacturing sector has upheld ‘efficiency’ as the mark of a highly optimized plant. But the topsy-turvy economic conditions of the past few years have forced industrial companies—and, indeed, all organizations—to rapidly consider their modus operandi to survive.
In today’s world, simply being ‘efficient’ and making a product at the lowest cost is not enough to succeed in the market. The post-pandemic disrupted supply chain presents an evolving and unprecedented rollercoaster of changing operating conditions. COVID-19-triggered lockdowns tested the plant’s resilience. A stimulus-induced economy fueled rapid growth and recovery.
Supply chain and labor disruptions continue to this day. Now, faced with economic slowdowns, inflation, and regional conflicts and unrest, manufacturers are under pressure to curb inflationary costs, increase efficiency, and become more agile than ever before. Plants that want to survive and thrive in a world of economic and supply chain curve balls are realizing that the operational concept of ‘efficiency’ must also be paired with an ethos of ‘responsiveness’. In this emerging industrial mindset, manufacturing plants must be ‘efficient’ whenever possible and ‘responsive’ when necessary.
Stuck in gear
While the business has many gears in its gearbox, the manufacturing plant is usually stuck in just one: efficiency. To maintain profitable margins, the supply chain strategy often revolves around insulating the plant from external volatility. In theory, protecting the process within the plant using a combination of inventory buffers, lead times, and supplier policies allows the plant to focus on a singular goal of increasing efficiency. But this led to an unfortunate side-effect: The protection from external variability created an insular, ‘within the four walls’ mindset. As long as production targets were met, corporate continued to treat the plant as a black box. This lack of visibility makes it difficult to engage the plant in modernizing the supply chain strategy to achieve greater agility and resilience.
Changing gears
Just like drivers use a gearbox to adapt to different road conditions, businesses need different gears to understand, plan, and execute during dynamic and disruptive business conditions. An agility-focused approach seeks to synchronize the plant with the supply chain strategy whenever it ‘changes gears’ so it can quickly adapt to changing conditions. In other words, the plant becomes more flexible to make changes as conditions warrant. When the plant is agile, it becomes a shock absorber for external volatility. Agility finds the tension between efficiency and responsiveness, allowing the plant to shift to each side, as necessary.
AVEVA’s internal research found that companies changed gears using the following eight levers in their business and supply chain strategy: inventory, capacity, time, segmentation, price, relationships, information, and cash.
Digitization in action
The responsive, gear driven mindset absorbs shocks from supply disruptions and is able to adapt to changing demands. Supply chain condition changes such as raw materials shortages, logistics issues, or demand spikes can have a massive impact on the manufacturing plant. While these may be hurdles for some plants, the ability to rapidly adapt to changing supply chain conditions turns those hurdles into opportunities. Quick changeovers allow brands to capitalize on market conditions and run at maximum capacity. AVEVA has worked with world-leading companies to implement digital manufacturing tools, providing their plant and production networks with a range of options to support an agile supply chain strategy.
An illustrative case-in-point is Graphic Packaging International (GPI), whose traditional scheduling capabilities relied on tribal knowledge and made it challenging for the firm to commit capacity to customers. GPI implemented advanced planning and scheduling to increase changeover visibility, reduce scheduling errors, and make data-driven decisions. Now, scheduling decisions are automated and based on company KPIs, not intuition, which enabled the company to meet capacity goals, reduce unit costs by 6 percent due to increased OEE, and save US$16 million annually.
In another example of how digital tools can elevate plant agility, F&N Dairies (FND), which produces three million cans of milk per day, realized that today’s customers want more from the brands they purchase. Quality, traceability, transparency, and sustainability are just a few of their requirements, and consumers are willing to put their money where their values lie. Quality is critical to maintaining consumer trust, but tracing parameter deviations was a manual process for FND operators. The existing paper-based system was error-prone and prevented operators from quickly performing root cause analysis. Using a mix of a data historian, batch management tools, and an MES solution, FND achieved digital tracking and traceability. These digital tools enabled the dairy to reach its production goal of 2,500 cans per minute, reduced quality traceability report time from four hours to one minute, and helped the plant achieve 100 percent first-time quality, which is a lean metric indicating that parts are manufactured correctly the first time without inspection, rework, or replacement.
What’s more, Kellogg’s, one of the world’s largest food manufacturing companies, has increased efficiency, enabling more digital ‘gears’. Kellogg’s holistic approach to digital transformation focuses on the end-user. The company’s program blends engineering, IT, and operational organizations to turn data into information that its teams can use to make improvements and increase efficiency. Kellogg’s data infrastructure enables operations data to be used in other applications, such as quality checks or packing line analytics. Operators can easily use these applications to understand how a production line is performing, including which products are being produced, changeover speed, losses, and supply levels. With easy access to efficiency, uptime, downtime, and critical loss data, users can identify common themes to make global improvements.
As this small handful of real-world case studies amid many others shows, the potential for digital manufacturing tools to elevate plant performance in tumultuous times is immense and wide-ranging. Those organizations that focus on responsiveness, as well as efficiency, by mapping new-world ‘gears’ will be best poised to take advantage of the myriad opportunities presented by the post-pandemic world.
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Sree Hameed |
Image Source: Magic Wand Media
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