Greg Rosenke
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Are You Using Analytics as Building Blocks?

May 1, 2020
Cloud offering serves as a pivotal building block as manufacturers pursue digital status.

Operating within a truly digital environment might be the goal for manufacturers, especially as customer expectations continue to evolve, creating pressures to deliver in ways that are difficult (if not impossible) to accomplish when manual processes are the norm.

The reality is many factories today still have large proportions of manual work. And, the reasons for this reality are quite clear: successfully deploying manufacturing technology is often costly and takes time to deploy and optimize. Significant skill shortages exist, meaning even after deployment many organizations struggle to realize the anticipated benefits. And the pressures to cost effectively produce quality products within a changing regulatory environment remain making sweeping operational changes difficult at best.

This isn’t to say that there has not been significant progress. There has been. Automation is growing. Data collection, and often limited utilization, continue to improve. People understand that manufacturing technology drives future success.

However, for many manufacturers, the idea of becoming a digital producer capable of mass customization is still in the distant future. Even in environments with modern machinery complete with connected networks, there's a lot of focus on the importance of the information from people within the factory. And that's generally the place where most manufacturers need to start if they want to drive the type of improvements that will eventually lead to seamless digital environments.

Big picture perspective 

For the digital journey to succeed, organizations ultimately need digestible components that enable it to methodically progress towards the end goal. Having a way to dynamically make sense of the data collected across diverse environments enables a manufacturer to make better decisions is key component, explains Mark Carleton, CEO of MESTEC.

“Manufacturers need tools that empower them to give the people on the factory line the type information that actually matters to them,” he says. “For instance, insights into what operations are running late, what quality checks are showing failure trends or even which machines will soon run out of material. It's really about addressing every stage of the manufacturing lifecycle.”

Leveraging a SaaS-based model, MESTEC provides out of the box analytics and dashboards that allow manufacturers to address daily performance issues and identify opportunities for improvement. MESTEC extracts information from whatever technology a company already has in place, such as ERP systems, in order to provide manufacturers with detailed planning, including honing details in a way that provides actionable insights. As such it excels in environments where there is a mix of people and machinery and across industries where significant manual inputs and compliance elements exist.

Moving MESTEC’s legacy on-premise infrastructure to the cloud that has zero downtime allows it to more strategically focus resources on innovating tools to improve manufacturing quality, cost, and delivery performance. As part of its offering, MESTEC leverages Oracle Autonomous Transaction Processing which patches, maintains, and tunes itself, providing a more secure environment that frees up resources to spend more valuable time on customer services and training. “With Oracle, we have greater flexibility to auto scale capacity up and down in seconds depending on demand and can very easily and quickly onboard new customers and assume less risk with automatic disaster recovery,” says Carleton.

“We model the whole of the manufacturing lifecycle from defining the manufacturing processes in detail including addressing planning constraints or recognizing what resources are needed for each operation,” he says. “It understandably takes a wealth of information to build the model. The goal is to use data to allow you to keep track of what is going on in real time versus manual procedures that lack accuracy.”

Bottom line, data is only powerful when the organization has a way to leverage it for actionable insights. The type of insights that drive productivity improvements and refine how businesses operate.

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