Five Ways Augmented Intelligence Can Improve Manufacturing

Posted on 31 Mar 2020 by The Manufacturer PR Service

Manufacturers are looking to capitalize on new insights from smart machines and sensors to gain time-to-market, cost, production efficiency, or quality advantages. By IQMS/DelmiaWorks Principal, Louis Columbus.

The challenge is extracting meaningful information and insights from the vast amounts of data generated by these technologies. That is why more manufacturers are turning to “augmented intelligence” and applying advanced analytics techniques to data stored in their manufacturing execution system (MES), real-time process and product monitoring, quality management, and enterprise resource planning (ERP) solutions to gain a competitive edge.

Why Augmented Intelligence Is Urgently Needed Now

What’s driving the adoption and growth of augmented intelligence is the need every manufacturer has to gain greater control, coordination, and visibility from every shop floor to every supplier acorss the entire business. By capitalizing on the volumes of data generated every day across their production operations, manufacturers are removing the barriers holding them back from achieving their financial, production, and quality goals.

To maximize the value of their data, manufacturers need to delve deeper into their operations than their pre-built dashboards, metrics, and key performance indicators (KPIs) allow. This means augmenting their reporting with real-time process and product monitoring and advanced analytics, including machine learning, to cull deeper, more timely insights into their operations.

Augmented intelligence enables manufacturers to go beyond knowing what is happening with their costing models, production scheduling, shop floor productivity, yield rates to understanding why. This in turn arms manufacturers with the knowledge on how to address these trends by improving production efficiency, quality, yield rates, and more. And that is a far more potent strategy for rising above competitors than any price drop or price war. Knowledge saves margins, and saved margins save companies.

Augmented intelligence is not a replacement for human decision-making. Instead, it helps manufacturers to become true learning organizations. By embracing augmented intelligence, a company has the foundation for turning its operation manufacturing operation into one that profoundly values learning, continual improvement, and the willingness to keep questioning how every aspect of production can be improved.

Where Augmenting Intelligence In Production Pays Now

The key to surviving today lies in knowing how every phase of production impacts overall manufacturing efficiency for a given plant while also tracking each phases’ combined contribution to reducing scrap, improving product quality, and meeting production schedules. The greater the uncertainty in the global economy, the more certainty every manufacturer needs to have of its operations. COVID-19 is a harsh wake-up call that manufacturers can’t rely on disconnected, disjointed systems or, worse, attempting to run a production plant on Excel spreadsheets.

Manufacturers need to start reinventing themselves now. A great place to begin is by looking at the approaches that have worked for other manufacturers and capitalize on their lessons learned. Here are five of the critical areas where manufacturers are relying on augmented intelligence to improve their operations.

Use augmented intelligence to synchronize diverse manufacturing systems. This is critical to breaking down the data silos that typically hold manufacturers back from greater efficiencies and cost savings. The first step to improving production operations is to define and implement a consistent, scalable intelligence platform that can capture, aggregate, and act on manufacturing data in real time. Having a unified, real-time analytics reporting system that can pull from different data sources is critical to overcoming the challenges of orchestrating key business processes, such as new product development, across multiple parts of the organization—from design to the shop floor, sales, and customer support.

Make real-time process and product monitoring the cornerstones of augmented intelligence. When using real-time data in combination with advanced analytics, manufacturers can gain the timely insights needed to achieve more significant cost optimization, higher quality, production improvements, and optimized maintenance, repair, and operations (MRO) strategies. Real-time process and product monitoring can also help pinpoint which machines on a shop floor need maintenance to improve production effiency, product quality, yield rates, and machinery and plant-wide utilization rates.  

Adopt machine learning within predictive analytics applications across shop floors by using real-time process and product monitoring data sets to fuel the development of useful machine learning models in manufacturing. Machine-learning algorithms are now available from a range of ERP, inventory management, MES, and production scheduling software providers. This emerging class of machine-learning-based predictive analytics applications will lead to more efficient inventory reconciliation via more accurate tracking of production time, downtime, total parts created, rejects, and parts.

Replace brute-force MES production scheduling with augmented intelligence to optimize production schedules down to the work center, operator, and material level. The core components of an MES—including Planning and Scheduling, Bill of Materials (BOM), Finite Scheduling, Shop Floor Control, Production Reporting, and Quality—each produce valuable data. Aggregating the data from all of these systems to see how an MES can improve production scheduling and efficiency is possible today. It can alleviate the need to take a brute-force, iterative, trial-and-eror approach to enhance a production schedule over time.

Apply augmented intelligence to optimize production workflows for highly customized, engineer-to-order (ETO) products while overcoming the constraint challenges of improving production efficiency. Doing so can help minimize the complexity around synchronizing production scheduling, engineering, and manufacturing to customers’ inbound order requirements. Augmented intelligence can free up manufacturers to manage custom configurations over their lifecycle, instead of as a special order or project for which they have to make exceptions.

The greater the uncertainty manufacturers face, the more they need to consider how they can apply augmented intelligence to become more resilient. Only by re-engineering or reinventing themselves by first creating a unified data platform that provides a 360-degree view of all the production operations can they grow competitively stronger in an uncertain world. Augmented intelligence is the path to knowing how every phase of production contributes to the goals they need to achieve now and in the future.

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