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Operational Efficiency Underpins Manufacturing Trends

Steve Bieszczat
By Steve Bieszczat Chief Marketing Officer, DELMIAWorks, Dassault Systèmes
Robot OEE

For the past few years, much of the manufacturing sector faced an economic bubble where consumer demand outpaced production. But that bubble has passed. Customers’ consumption patterns have returned to more typical patterns, leaving many manufacturers to face an excess of production capacity and costs. In response, they are tabling the produce-at-all-cost manufacturing strategies they previously adopted to meet historically high levels of demand and putting a renewed focus on operational efficiency through 2024.  

Expanded Automation

More manufacturers will take advantage of advances in automation to offset the continued challenges with labor costs and availability. In particular, collaborative robots, or cobots, are tipping the automation value equation. They are multi-axis and have articulated wrists, which means they can do intricate tasks. They are safer to be around, and they are easier to program and train. Because cobots are easier to set up, require less extensive safeguards, and do not need expensive technicians to program and maintain them, they are driving down the costs of automation.

At the same time, artificial intelligence (AI) training systems running in the cloud allow companies to get greater value out of the machine vision systems they’ve been running for years. Additionally, robotics as a service from companies, such as Rapid Robotics, are being utilized on a greater variety of jobs. Together these factors are pushing the return on investment (ROI) for automation up to new levels.

Workforce Enablement

Manufacturers are also using technology to attract, empower and retain valued employees. So, we’ll see a greater investment in manufacturing execution system (MES) systems that not only track production but enable workers to quickly learn to perform new tasks with work center-based training and guided operations.

These MES systems also alert workers to exceptions across multiple work centers, freeing them from mundane watch-and-wait tasks at each work center.

We also see increased use of enterprise resource planning (ERP) solutions for advanced warehouse management where paperless, scan-based material identification and tracking, plus directed put-away and pick operations, keep warehouse workers more productive and engaged.

Vertical Integration and Consolidation

Merger and acquisition (M&A) deals in 2024 focus on advancing strategic goals in two synergistic areas. First is meeting the demands of upstream customers to reduce the number of vendors they work with. Second is the ability of consolidators and integrators to eliminate redundant sales, marketing, front office, production and distribution costs, while also building the one-stop-shop supply chain businesses that original-equipment and tier-one manufacturers prefer. These M&A trends are driving an increase in ERP system adoption and consolidation. Investors and ownership groups need clear visibility and control across larger and more complex operations. ERP not only offers that visibility; it also provides a tool for implementing consistent business practices across multiple operating facilities.

AI Drives Decision Making and Execution

Generative AI tools like ChatGPT offer some tactical benefits, such as helping to create better training guides or work instructions. However, the greater impact will come as manufacturers utilize existing AI- and machine learning-driven tools to achieve operational excellence and efficiencies. These tools include forecasting, automated scheduling, MES, statistical process control, predictive maintenance, and active alerts and workflows.

Two factors will accelerate the adoption of AI- and machine learning-driven tools. First, a generational knowledge shift is underway as more seasoned analysts and planners retire, taking with them a lifetime of hands-on experience. The existing AI-driven tools in most manufacturing environments are becoming essential to replace these retiring experts. Second, businesses that are vertically integrating and consolidating face new levels of complexity that require data processing capabilities and capacities well beyond those of human analysts. Here, the ability to execute AI- and data-driven planning and control over processes, such as forecasting and scheduling production, is becoming essential for success.

Sustainability as an Operational Asset

A growing number of large manufacturers, retailers and other businesses have published goals to be carbon neutral by 2050. And, because a company’s carbon footprint is determined by both its own production and the production and operations of its supply chain, these large corporations need to start measuring and claiming reduced emissions from their contract and supply chain manufacturers. This will make sustainability and carbon footprint tracking and reporting programs key supply chain concerns for manufacturers in 2024 and beyond.

Notably, having a formal sustainability and carbon footprint management plan not only helps manufacturers to gain preferred vendor status; it can also drive operational efficiencies. For example, reducing carbon footprint can improve a manufacturer’s bottom line, since the top purchasing spend often includes raw materials and energy consumption, the largest contributors to carbon emissions. While there are specialized systems for tracking sustainability performance against goals, manufacturers can use their existing ERP systems to calculate their carbon footprint and related costs much as they already do for inventory. This is lowering the barrier for manufacturers to reduce their carbon footprint in order to establish preferred vendor status and increase operational efficiency—all while protecting the environment.

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