Is SAAS for Overall Equipment Effectiveness (OEE) Implementation the Key to Unlocking Immediate ROI?

by Randy Blaylock, on May 14, 2018 2:58:09 PM

AutomationCom200 Article Published May 4, 2018

The capital required for old-fashioned OEE software implementation is a thing of the past.  Manufacturers are constantly challenged to increase productivity, improve quality, and cut costs to successfully compete. Manufacturing technology, business intelligence, and plant-wide visibility ensures manufacturers overcome these pressures with real-time critical information to appropriate personnel with a single version of the truth.  There is universal agreement that OEE remains a powerful tool for manufacturing organizations interested in taking control of improvements toward manufacturing excellence.  The old model of OEE implementation was capital intensive and prohibited most small and mid-sized manufacturers from using a well-respected tool.  The SaaS OEE is positioning itself as a game-changer by inviting ALL manufacturers to utilize these most needed metrics. 


Only when data is captured directly from machines/equipment and organized in a manner that drives peak performance is the information useful. Because no two manufacturing facilities are identical, it is vital that visual content be presented on any web-capable device such as large overhead displays, PC’s connected to the network, and mobile devices. 

Only when users visualize and comprehend data from a variety of Key Performance Indicators (KPIs) are different areas of the plant floor reported, recognized, and acted upon. Reports and dashboards in new technologies capture process and production trends using "smart widgets" from Analytics. Notification features pinpoint the most concerning problems allowing plant personnel to take immediate action.

OEE Focus on Streamlined Data Flows

Streamlining the collection of key performance indicators from shop floor equipment and operators can now be interlocked to machine controls to ensure events are properly classified. Until very recently and without a pay-as-you-go SaaS (software as a service) payment model, small and mid-sized manufacturers could not achieve a rapid ROI (return on investment) using OEE solutions for industrial hardware and software installations.


KPI Metrics

Even the smallest manufacturers with a dozen machines monitored can cost-justify a monthly paid SaaS OEE lean affordable option.  Improvement projects to maximize ROI is central to all lean manufacturing and industrial projects. If staffing is significantly different on different shifts, then the OEE can be used to examine the results for a single shift (all the parameters would need to be allocated appropriately among the various shifts) and then accumulate the total savings for the two different sales scenarios.

Greater precision is developed by using actual OEE data differentiated by product run and by work station. Future monitoring and proactive use of the information provided by an installed system significantly improves accuracy of alternatives; these data assists leadership by monitoring each machine as producing a finished product that has an average Cost of Goods Sold (COGS) and profit contribution (IFO or EBITDA). Typically, product flow maps should be used to review the business case for the flow recognizing that the only time a profit is made is when the final output of the stream is actually sold. Plant Throughput is used to look at the changes in expenses (materials and labor on key machines) and income (Throughput accounting). One critical metric to review is the Number of Reduced Shifts required on key machines for the Sell Same Volume. The result is often far fewer Overtime shifts or shift improvement. When waste or scrap is improved, OEE improves; the result, less material needed.

Improvement input for the various parameters should be selected representing the gap between current performance and World Class. Once data collection is in place and critical data is obtained by product run, an in-depth product flow line analysis can be generated (Financial OEE) which will clearly define IFO results by product to determine contribution by constraint minute.

Once total savings are computed, the number of weeks for the project to be “paid back,” must be recalculated, using the following formula:

(Project cost ÷ (Total Savings ÷ number of weeks of operation per year)) = number of weeks (of improvements achieved) to breakeven.

Identify Quality Issues Quickly

Gaining 24/7 real-time visibility into production constraints, bottlenecks, and quality concerns allows progressive manufacturers to assign root causes to downtime events, classify idle time, and enter scrap codes.  It also ensures an immediate notification to key personnel via text and email when quality issues occur.

Aspirational Production and Productivity Improvement Targets

Avoiding poor quality and the capacity to respond quickly is vital; however, setting aspirational production targets and benchmarks per asset and resource must be an authentic and forward-thinking aspect to next generation OEE solutions. The capacity to configure dashboards to display current needs and historical trends becomes a foundational building block to optimize lean manufacturing with continuous process improvement planning.        

With an OEE solution, data is captured directly from machines/equipment and organized in a manner that drives peak performance. Visual content can be presented on any web-capable device such as large overhead displays, any PC connected to the network and mobile devices.             

The outcome is always increased productivity. When production and operations managers obtain summary aggregation and drill-down visibility of assets, a quantifiable boost in productivity results.

About the Author

randy-headshotRandy Blaylock, VP of Sales for eFlex Systems, has over 30 years of consultative selling experience and has a reputation as a top solution sales professional and team leader.  He has many years of experience in engineered manufacturing and material handling equipment, which gives him an extensive understanding of manufacturing processes and related material movement throughout a wide range of industries. Randy has an engineering and design background which gives him a unique perspective to fully understand the impacts of software and technology in manufacturing.  

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