Toward Zero Blog for Digital Transformation Best Practices

Over the years, our smart manufacturing consultants and systems engineers have narrowed down the top three reasons why manufacturing companies say they turn off OEE software:

1. Not enough data - Some OEE systems take up too much operator time to collect data and enter it into the system. Data is often spotty or inaccurate, making the OEE software useless.
   

Data, particularly machine data, is a foundational component of every smart factory or OEE initiative. It fuels analytics, triggers actions ahead of problems or shutdowns, and provides insight for continuous improvement. Many companies start the smart factory journey with an automated OEE system because it’s a natural progression with a set of metrics they’re already familiar with. Despite advances in automated data collection and production analytics, a lot of manufacturing executives are still at odds about exactly which machine data is required to calculate OEE. Unfortunately, a lot of projects get sidetracked early on as stakeholders try to utilize every piece of machine-generated data from the multitude available. A more pragmatic approach is to apply machine data based on priorities around business goals. To that end, capturing the machine data required for OEE is a critical early activity for most smart factory initiatives.

Does your company think of production planning and scheduling as simply a plant process to convert orders into a daily manufacturing plan?  If so, it might be missing out on some of the greatest opportunities to improve on-time delivery, optimize inventories, and increase profitability.  Over the years I’ve observed repeatedly how data helps companies eliminate conflicts, set priorities, and bring people together around shared objectives.  The longstanding plant-supply chain balancing act is a common one among manufacturers, and for the last five years I’ve had a front-line view of how world-class companies use data to overcome plant-supply chain conflicts.

Not everyone in manufacturing roles has a lot of experience with Lean or OEE.  In fact, here we are nearly 40 years after OEE was first described in Introduction to TPM: Total Productive Maintenance , and people are still asking how to calculate OEE.  Everyone has a story about how they learned about OEE and Lean, including me.  What’s fascinating is that despite all that’s been written on these topics, manufacturing companies still struggle to capture significant value from Lean tools and OEE calculations.

Over the years, our smart manufacturing consultants and systems engineers have narrowed down the top three reasons why manufacturing companies say they turn off OEE software:

1. Not enough data - Some OEE systems take up too much operator time to collect data and enter it into the system. Data is often spotty or inaccurate, making the OEE software useless.
   

Data, particularly machine data, is a foundational component of every smart factory or OEE initiative. It fuels analytics, triggers actions ahead of problems or shutdowns, and provides insight for continuous improvement. Many companies start the smart factory journey with an automated OEE system because it’s a natural progression with a set of metrics they’re already familiar with. Despite advances in automated data collection and production analytics, a lot of manufacturing executives are still at odds about exactly which machine data is required to calculate OEE. Unfortunately, a lot of projects get sidetracked early on as stakeholders try to utilize every piece of machine-generated data from the multitude available. A more pragmatic approach is to apply machine data based on priorities around business goals. To that end, capturing the machine data required for OEE is a critical early activity for most smart factory initiatives.

Does your company think of production planning and scheduling as simply a plant process to convert orders into a daily manufacturing plan?  If so, it might be missing out on some of the greatest opportunities to improve on-time delivery, optimize inventories, and increase profitability.  Over the years I’ve observed repeatedly how data helps companies eliminate conflicts, set priorities, and bring people together around shared objectives.  The longstanding plant-supply chain balancing act is a common one among manufacturers, and for the last five years I’ve had a front-line view of how world-class companies use data to overcome plant-supply chain conflicts.

Not everyone in manufacturing roles has a lot of experience with Lean or OEE.  In fact, here we are nearly 40 years after OEE was first described in Introduction to TPM: Total Productive Maintenance , and people are still asking how to calculate OEE.  Everyone has a story about how they learned about OEE and Lean, including me.  What’s fascinating is that despite all that’s been written on these topics, manufacturing companies still struggle to capture significant value from Lean tools and OEE calculations.