4 Innovative Ideas to Improve Manufacturing Productivity

Strategic Technology Innovations for Improved Manufacturing Productivity Processes

Looking for innovative manufacturing improvement ideas to assist with productivity? More advanced technology equals higher workforce productivity—this is the simple equation that drives enterprise strategy for many manufacturing leaders. But technology and productivity do not always increase in direct correlation with one another. Instead, it is only by strategically investing in the right technology solutions that manufacturers can ensure effective productivity gains for their workforce.

With technology refresh cycles renewing rapidly at a pace of only 4 to 5 years, manufacturers need to understand how best to keep pace with the adoption of strategic solutions that will result in long-term, factory-wide productivity benefits. Let’s discover how to improve manufacturing productivity with factory process improvement ideas.

Staying on Top of Manufacturing Technology Trends

Evaluating top industry trends gives manufacturers a glimpse into the future of industrial technology and which solutions are necessary to unleash long-term productivity benefits. Today, overarching manufacturing technology trends include:

Embedded intelligence and intelligence at the edge. By moving data processing and analytics to where manufacturing is actually taking place, factories can ensure better connectivity and a better flow of actionable data. Today, 75% of the data generated within the manufacturing industry is generated at the edge.
Tools for error cognition. Of the data generated at the edge, only 6% is actioned. That’s because humans simply don’t have the manpower to accurately review the abundance of edge data and recognize potential patterns or problems.
New, user-oriented business models. Finally, manufacturers are realizing that the future is not solely about the product being utilized—it's about how a product is being used and how it ties to business outcomes such as improving productivity while reducing the cost of quality. Instead of buying a system or a machine, people would subscribe to the machine and buy the machine as a service, where the capital cost of the machine is not on the balance sheet. Instead, they would pay an operational cost, on a monthly/quarterly/yearly/annual basis.

In addition to trending technology insights, ‘technology enablers’ are another key factor to consider in the technology adoption process. Today, these enablers include ubiquitous sensing, cloud computing, digital twins, predictive analytics, and more—each of which will influence the creation, adoption, and convergence of key manufacturing technologies and the landscape of workforce productivity. Ultimately, these enabling concepts and trends will converge with AI models for deep learning to drive new opportunities for manufacturing productivity, like more connected field service, smarter edge applications, AI-based cybersecurity, and more.

Understanding Digital’s Impact on Modern Manufacturing Productivity

While these trends and enablers are crucial points of consideration for tech adoption and subsequent productivity gains, manufacturers should also look to their most prevalent productivity pain points when considering where to begin with productivity improvements.

For example, manufacturers face many information challenges ranging from the collection of data, to optimizing its application, to ensuring its quality. They are also bogged down by equipment maintenance that must be completed to prevent unplanned downtime. Another pressing challenge is the shortage of skilled workforce. In fact, Frost & Sullivan estimates that 25% of the industrial engineering workforce is 55 years or older. On top of the workforce shortage, it is also noted that the niche skills necessary to perform particular jobs will become outdated in just a few years. Safety and cross-factory communication also top the lists when manufacturers discuss their most pressing challenges.

The most universal obstacle to improve manufacturing productivity processes, however, is the convergence of these smaller challenges. It is the fracturing of the manufacturing value chain, which takes place as factories attempt to keep costs low, innovation high, and consumer checkpoints frequent.

Luckily, digital innovations are helping manufacturers unify the segments of their value chain once more. For example, by developing a strong foundation of Industrial IoT (IIoT) capabilities, factories can increase necessary visibility and traceability within the manufacturing product flow. Additionally, by shifting toward digitalization in a factory, manufacturers can empower operators with interactive, visual work instructions to optimize production flow—which has been proven to improve workforce productivity by 10 to 12%. Finally, by instituting connected manufacturing intelligence and the use of analytics to drive alerts, manufacturers can keep data flowing between factory sites, and between factories and consumers.

Rely on Strategic MES Solutions to Drive Factory-Wide Productivity

Clearly, strategic technology adoption can empower the workforce to drive tangible benefits to manufacturing enterprises—all while promoting areas that elevate job satisfaction. There is one technology, however, that stands out among the rest as a key piece of the productivity puzzle: Manufacturing Execution Systems (MES).

With an MES system, intelligence can be gathered horizontally and vertically from machines, devices, systems, and people. The most advanced MES system will facilitate transactions, processes, and logistics seamlessly, thereby collecting and analyzing data that can be leveraged by the entire enterprise, always keeping insights in context for maximum utility. Knowing exactly what data means and where it’s coming from, regardless of the data source, is where productivity improvements in the manufacturing industry truly begin.

This vision of an MES-enabled, productive IIoT ecosystem isn’t as far away as manufacturers might think. For instance, Aegis and its FactoryLogix® MES system have worked with the IPC association and hundreds of machine vendors, solution providers, and manufacturing companies to create and publish a game-changing, consensus-based IIoT standard known as CFX (Connected Factory Exchange). This “plug & play” standard rapidly eliminates the need for middleware, enabling any manufacturer of any size to realize the true productivity benefits of Industry 4.0—without exorbitant time or cost.

But how exactly are FactoryLogix and CFX revolutionizing manufacturing productivity? Unlike other IIoT standards, CFX defines the content being communicated and conveys meaning between disparate manufacturing languages, making it the ultimate standard for manufacturing productivity in any industry. Also, other standards have traditionally tried to define data depending on the machine type, but machines and devices are no longer monolithic. This is where the “building block” concept of the CFX standard comes into play. The standard uses modern coding technologies and data schemas to define the lowest level of activity (i.e. stapling; copying; collating). This eliminates the proprietary scenario in which one company is defining how a function should be done one. The data is not defined by any one type of machine vendor. There is one agreement as to what stapling data should look like and then you can build the base components together, like blocks, to get the data you desire without worrying. This is what makes is applicable to any industry.

The CFX standard isn’t the only way Aegis’ modern MES system is ramping up productivity for factories around the world. To learn more about how to strategically improve quality and increase productivity in manufacturing—and how Aegis FactoryLogix enables visual work instructions, augmented reality, lean materials management, traceability, and more to accelerate productivity in proven ways—watch our Frost & Sullivan Webinar, “Accelerating Workforce Productivity with Manufacturing Technology Innovations.”