Using OEE Data to Improve Manufacturing Operations

Utilizing OEE Knowledge to Enhance Manufacturing Operations

Using OEE Data to Improve Manufacturing Operations
Utilizing OEE Knowledge to Enhance Manufacturing Operations

As producers proceed to sort out the challenges of the trendy working setting, extra of them are turning to information and expertise to resolve present issues and plan for the long run.

A scarcity of labor, the continued provide constraints, and excessive demand for merchandise are pushing producers to rethink how they run, monitor, and optimize their manufacturing environments. A spot the place seat-of-the-pants choices and guesswork don’t reduce it, trendy manufacturing requires a data-centric strategy that helps corporations determine issues, leverage alternatives, and pivot accordingly.

Checking all these containers within the fast-paced manufacturing setting isn’t simple, however expertise has superior to the purpose the place it may possibly assist corporations enhance operations with out having so as to add extra labor, gear, and manufacturing traces. Beneath fixed stress to do extra with much less—and with much less downtime—corporations are utilizing information analytics to get extra productiveness out of their present services in a secure and predictable method.

In fact, steady manufacturing course of enchancment requires entry to all information, not all of which is simple to seize, combination, or make actionable. With out this information, course of inefficiencies, sudden machine downtimes, and manufacturing losses emerge. By monitoring general gear effectiveness (OEE) and manufacturing traces, corporations get all the knowledge they want to have the ability to readily determine bottlenecks and factors of failure, and to make sure course of optimization throughout all manufacturing traces.

What Is OEE?

OEE is a way to measure manufacturing productiveness. It helps to determine the manufacturing time that’s actually productive and offers the knowledge a producer wants to have the ability to readily determine bottlenecks, factors of failure, and areas of alternative. With these information factors at their fingertips, corporations can optimize processes to satisfy the calls for of as we speak’s operational setting.

A typical metric utilized by producers, OEE scales from zero to a 100% however is greater than only one single quantity. Three various factors go into it: efficiency, availability, and high quality. Collectively, these components make up a producer’s OEE worth. Leaders of their fields are inclined to run within the 85% vary, whereas corporations which are enjoying catchup normally have OEEs that vary from 30% to 60%.

At its easiest, OEE measures manufacturing productiveness and tells corporations simply how successfully they’re (or aren’t) using their gear. For organizations that make investments a lot of their capital in gear—after which don’t use these property to supply revenues or expertise numerous downtime on that gear—low OEEs are pretty widespread.

A scarcity of labor, ongoing provide constraints, and excessive demand for merchandise push producers to rethink how they run, monitor, and optimize their manufacturing environments.

An organization may need a manufacturing line put in, but when this CapEx expense is just getting used for 3 hours throughout a shift and solely at half-speed, then the corporate shouldn’t be utilizing its property successfully.

Hold the machines working

When gear goes down on a manufacturing line, the whole lot from stock ranges to provide chain administration to customer support could be negatively impacted. Staff are left idle whereas the machines are fastened, throughput can come to a halt, and efficiency targets are missed. By Deloitte’s estimates, manufacturing downtime prices corporations about $50 billion yearly, whereas poor upkeep methods could hinder manufacturing functionality by wherever from 5% to twenty% for a single plant.

Studying the reason for the downtime is step one in lowering these numbers and retaining the machines working, and it begins with understanding the OEE of these property. Normally, the basis of the issue is {an electrical} challenge, a mechanical malfunction, or operator error. If it’s {an electrical} challenge created by an extreme variety of unfastened wires within the equipment, for example, then higher coaching {of electrical} division staff is perhaps so as.

With correct insights into why the machines are failing (AKA fault metrics), corporations can readily tackle the problems and decrease general downtime. The issue is that not all corporations have visibility into these fault metrics. Even for those who do, their OEE perception is perhaps targeted solely on the quantity, with out actually understanding why it continues to fall or what to do about it. Not a lot could be performed with the OEE quantity with out consciousness of the areas which are in want of enchancment.

Geared up with the appropriate information assortment and evaluation instruments, nonetheless, the identical firm positive factors excessive ranges of visibility over efficiency issues, bottlenecks, throughput constraints, and different challenges. Utilizing the information, producers can successfully sort out these points and enhance their productiveness and uptime. This, in flip, will lead to a better OEE quantity.

Utilizing information to optimize productiveness

A number one producer of sensors and sensor options for industrial automation purposes, SICK makes sensors which are used on the store flooring to gather and analyze the information that producers want to have the ability to run their operations at optimum ranges. Utilizing key information factors like working standing, product depend, and high quality counts, SICK’s options encapsulate the insights in a software program analytics platform that gives OEE calculations.

Producers use the platform to see how properly their traces are performing. With just a few sensors and communication enabled by OEE analytics, producers achieve entry to real-time and historic insights into significant KPIs that they’ll use to stabilize and/or optimize productiveness.

SICK presents each a typical Package deal Analytics Platform and a Fast Deployment Equipment (RDK). Utilizing both of those choices, producers can begin with only one machine after which scale as much as a whole manufacturing, packaging, or different line.

Firms can begin small and zoom into the realm of preliminary concern, understanding that the answer can then be expanded to different areas of the ability. By starting at one finish of the plant and making their method throughout the ability, corporations can enhance operations, efficiency, and high quality as they go.

The OEE Fast Deployment Kits mix software program and {hardware} to assist corporations rapidly start utilizing manufacturing information to drive higher enterprise choices. The answer’s OEE analytics and product lifecycle administration (PLM) instruments have been preconfigured and allow quick, simple commissioning and set up. They assist corporations drive enchancment by offering a greater understanding of manufacturing losses and cut back seemingly advanced manufacturing issues to easy, accessible data that producers can use to enhance effectivity and decrease working bills.

Key metrics that the answer displays embrace availability, shift period, elapsed shift time, machine/system uptime, efficiency, anticipated and predicted outputs, precise outputs, and high quality output. Utilizing real-time monitoring of those and different vital OEE metrics, corporations achieve a greater understanding of general system habits and traits, determine goal areas for enchancment, and make higher, datadriven enterprise choices.

Geared up with these precious insights, corporations can reallocate labor to different value-added duties, give their customer support and gross sales groups extra correct data, outline roles for who can entry the information, enhance their gross sales revenues, and achieve an edge on their opponents. They will additionally take a extra proactive strategy to machine upkeep and stability, which in flip helps larger gear uptime.

Producers are beneath stress to supply extra whereas additionally retaining methods working till they fail, however it is a flawed strategy. One line that goes down can throw off a complete manufacturing schedule, which then pushes everybody into catastrophe restoration or reactive upkeep mode.

Don’t simply go together with your intestine feeling

With an analytics-based OEE answer in place, producers understand how properly they’re acting on all three metrics—availability, efficiency, and high quality—and have an overarching view of how properly they’re doing.

Primarily based on that information, corporations get a grade score as they make enhancements like mechanical changes or operational adjustments to straightforward working procedures (SOPs). Then, they’ll use their OEE numbers to evaluate what’s or isn’t working and make additional changes as wanted.

This data-based strategy is way more efficient than the “intestine feeling” methods that many producers depend on to maintain their traces up and working. Slightly than simply guessing at what would possibly work, they’ll use the information to check out numerous steady enchancment initiatives on their traces and instantly see how these shifts affect efficiency.

Giant meals producer runs smarter with OEE

When one high-volume producer and distributor of assorted native and genuine pre-packaged gourmand meals throughout 37 nations seen discrepancies within the quantity between shifts, it realized that it wanted a fast method to determine manufacturing metrics and bottlenecks. Traditionally, it carried out handbook course of counts of the manufacturing traces between shifts—an strategy that created quite a few operational inefficiencies.

For instance, handbook entry errors in manufacturing portions led to miscounts and inaccurate paperwork. These, in flip, decreased precise manufacturing quantity accuracy. The producer additionally couldn’t correctly monitor stock and manufacturing or predict manufacturing numbers with a excessive diploma of accuracy. This resulted in over- and under- producing efforts, each of which impacted its profitability.

Mixed, these inefficiencies had been affecting the corporate’s each day manufacturing and impeding its skill to satisfy rising buyer demand. Working with SICK, the producer started implementing OEE ideas. It upgraded its manufacturing line and carried out an information analytics answer, the latter of which might allow higher entry to information and insights into find out how to finest cut back dangers and challenges.

Utilizing SICK’s Fast Deployment Equipment, the meals producer gained a greater understanding of manufacturing losses. The encoder ensures that the machine is working and sends a sign to the SIG200 to substantiate this. Then, the product is counted utilizing presence sensors because it runs down a number of manufacturing traces concurrently. Lastly, the machine captures product information plus any lacking items or flaws within the manufacturing line and sends that data as much as the SIG200 for assessment.

As soon as the products cross high quality inspection, the completed merchandise are stacked for processing and transport. With this answer in place, the producer now has a baseline and might monitor real-time and historic OEE metrics over time, main to higher general machine availability and a better high quality product to supply its prospects.

Producers do extra with much less

A key metric for measuring manufacturing productiveness, OEE helps corporations determine losses, measure progress, eradicate waste, and enhance manufacturing gear productiveness. And whereas the OEE metric itself has been round and in use for a while now, for probably the most half corporations have been monitoring it on paper and Excel spreadsheets. Each approaches are liable to information entry errors in an setting the place three-second “micro stops” that repeat themselves could considerably impede general efficiency.

Utilizing sensors, information, analytics, and a user-friendly dashboard, SICK makes it simple for producers to measure OEE, tackle points, leverage alternatives, and implement a tradition of steady enchancment. These are key wins in a enterprise setting the place all corporations are beneath stress to maximise throughput and do extra with much less, and shutting down a line to put in new software program or {hardware} on it isn’t a workable possibility.

The RDK could be deployed even whereas the road is working, which is essential for producers that don’t have the posh of shutting down their operations. With RDK, the system is up and working, and gathering the information rapidly. This instantly reveals precisely why these micro stops or different points are occurring so producers can take the steps obligatory to enhance OEE throughout all three metrics—availability, efficiency, and high quality

Pictures courtesy of SICK

This characteristic comes from the e book AUTOMATION 2023 Quantity 3: IIoT & Trade 4.0.

About The Writer

Kevin Welsch is an business advertising and marketing supervisor and acts because the advertising and marketing liaison for SICK’s Manufacturing unit Automation Regional Gross sales Group, Oblique Distribution Channel with a give attention to shopper items, machine builders, electronics, and photo voltaic enterprise initiatives. Kevin is a seasoned promoting, advertising and marketing, and gross sales skilled throughout the industrial automation business.

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