• Main website
  • Case Studies Home
  • Case Studies
    • Green Belt
      • Example Green Belt Projects-Health Care
      • Example Green Belt Projects-Manufacturing
      • Example Green Belt Projects-Services
    • Black Belt
      • Example Black Belt Projects-Health Care
      • Example Black Belt Projects-Manufacturing
      • Example Black Belt Projects-Services
    • Master Black Belt
    • Lean Success Stories
  • Articles
    • LSS topics of common interest
    • Insights for Green Belts
    • Green Belt tool application examples
    • Insights for Black Belts
    • Black Belt Tool Application Examples
    • Lean Insights
    • Lean Six Sigma Leadership
    • For Master Black Belts
    • New to Lean Six Sigma
      • Lean Expert Basics
      • Six Sigma Basics
    • Leisure and Fun
  • Blog

Increasing Machinery Throughput With less Machines

machines

Consider the subsequent example. In the Midwest a production corporation with extra than 1,500 personnel labored a round the clock 24/7 schedule. The corporation manufactures a product this is sticky; it calls for a excessive-velocity, excessive-quantity manufacturing via one in all 14 distinct reducing and packing machines.
Four groups labored rotating 12-hour shifts on the ones 14 distinct machines. Employee morale turned into continually a trouble because of the lengthy shifts – in specific, a few personnel ended up running maximum weekends. At the time, the throughput performance turned into approximately sixty five percentage.

The finance branch calculated that if the throughput performance of the product multiplied to 70 percentage, sufficient might be synthetic in sixteen hours of manufacturing to satisfy client demand. Then the corporation may want to flow to a machine of eight-hour shifts – giving extra unfastened time to the employees and saving the corporation money.

In this excessive-velocity (extra than 2,000 portions a minute) environment, the product desires to go into the primary device in accurate alignment so that it will flow via a sequence of rotating steel elements, wherein it then meets – and is wrapped via way of means of – paper.

Over time, the product receives out of alignment because of its excessive velocity of motion. Due to its sticky nature, the product also can get caught at the steel elements of the equipment; this slows down or stops the technique as a whole. At that factor, an operator have to forestall the equipment, open up a tools field and clean out the jam via way of means of disposing of paper and cleansing off residual sticky product, or via way of means of troubleshooting thru some of different methods.

This gradual down or stoppage occurred approximately 5 to ten instances each hour according to device.

The operators are skilled and extraordinarily adept at locating and correcting the issues of the wedged equipment. They carry the technique again up as speedy as possible (and their velocity will increase over time), which improves the general performance and throughput of the line.

Variables of Efficiency
The plant engineers knew that performance various with product type – a few manufacturers are stickier than others. The stickier the product, the extra clogs withinside the gears of the equipment may be expected. Certain machines carry out higher than different machines. And a few operators are higher than others. But which of these variables turned into maximum important? And via way of means of how much?

Handpicked Content: Sustaining Improvement via way of means of Building a Quality Mindset
Answering those questions turned into critical – every 1 percentage motion on performance might store approximately $250,000 in step with the finance branch.

Data captured via way of means of application good judgment controllers on every of the machines blanketed what number of portions of product they wrapped and at what instances. The corporation had information on the subsequent variables:

The machines
The operators’ hours (operators check in thru a bar code on their badges after they start their shifts)
Pieces of product produced
Time to supply product
Reason (out of some given choices) equipment went down
Where (physically) the fault lay in the equipment
The corporation had to remedy the unique trouble of which variable turned into the largest driving force of performance loss the various following:

Machine
Product type
Operator
Hour of day

See full story on isixsigma.com

June 23, 2014   Benchmark Six Sigma
Case Studies, Example Green Belt Projects-Manufacturing, Green Belt Qualified
×

  • How to Build More Impactful Centers of Excellence
  • Manage Control Limits When Implementing Statistical Process Control

Categories

  • Articles
    • Black Belt Tool Application Examples
    • For Master Black Belts
    • Green Belt tool application examples
    • Insights for Black Belts
    • Insights for Green Belts
    • Lean Insights
    • Lean Six Sigma Leadership
    • Leisure and Fun
    • LSS topics of common interest
    • New to Lean Six Sigma
      • Lean Expert Basics
      • Six Sigma Basics
  • Case Studies
    • Black Belt Qualified
      • Example Black Belt Projects-Health Care
      • Example Black Belt Projects-Manufacturing
      • Example Black Belt Projects-Services
    • Green Belt Qualified
      • Example Green Belt Projects-Health Care
      • Example Green Belt Projects-Manufacturing
      • Example Green Belt Projects-Services
    • Master Black Belt
  • Featured Articles
  • Lean Qualified
    • Lean Success Stories
  • Project Management Articles
  • Uncategorized

Archives

  • April 2021
  • November 2015
  • April 2015
  • March 2015
  • February 2015
  • January 2015
  • December 2014
  • November 2014
  • October 2014
  • September 2014
  • August 2014
  • July 2014
  • June 2014
  • May 2014
  • April 2014
  • March 2014
  • February 2014
  • January 2014
  • December 2013
  • November 2013
  • October 2013
  • September 2013
  • August 2013
  • July 2013
  • June 2013
  • May 2013
  • April 2013
  • March 2013
  • February 2013
  • January 2013
  • December 2012
  • November 2012
  • February 2012
  • March 2011
Copyright © 2023 Benchmark Six Sigma