Blog

Oct

2017

"Lean Math: Figuring to Improve" Receives 2017 Shingo Publication Award

By MarkRHamel

The following is an excerpt from a Shingo Insititute press release dated September 7, 2017:

Sep

2017

Setup Reduction Strategy and Internal versus External Changeover Time

By MarkRHamel

$Changeover Reduction$

Sep

2017

Changeover Time

By MarkRHamel

Changeover time represents the elapsed time to changeover from the production/processing of one product or service to a different product or service. Admittedly, there is little math involved here. Some readers may scratch their heads and wonder why one would need a math entry at all! However, changeover time is important in the overall scheme of Lean Math and, with it, the principle of flow and pull. More specifically, internal changeover time (T∆i) is a critical driver of batch sizes, lead time, and intervals.

Jun

2017

Benchmarking and the Absolute Benchmarking Process Efficiency Ratio

By drmike

Neil always used to confound and shock me. He was always pursuing perfection. And I would always retort something like, “But, the real world isn’t perfect.”

Over the years, I slowly realized the value and wisdom of Neil’s mindset. It is consistent with traditional lean thinking (as long as it does not paralyze the PDCA cycle), and it helps drive innovation and the right thought process. I have found that lean thinkers not only benchmark themselves against the competition, they also benchmark themselves against perfection. This is where math can help.

Jun

2017

New Book, New Look, and New Content

By MarkRHamel

New Book. A handful of weeks ago, SME published our new book, Lean Math: Figuring to Improve. It is, and was, undoubtedly a labor of love…or at least the 444-page labor of Dr. Mike (aka Michael O’Connor) and me.

Aug

2015

Inventory Record Accuracy

By lloucka

How you measure Inventory Accuracy depends on where you stand.

Inventory

Pages

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Category Descriptions

The various categories that are listed on the sidebar and menu may be a bit obtuse. So, the following descriptions may be helpful.

Systems. It’s easy to get lost in lean tools and the related math. Lean practitioners remember that systems thinking is critical to maintaining the proper perspective and understanding. What kind of systems are we talking about? Well, stuff like Little’s Law, value stream analysis, process mapping, etc. These subjects, by their nature, reflect important inter-dependencies and with that…math.

Time. Lean is much about time and space. In fact, try stringing together a few sentences about lean without using the word, “time.” Pretty challenging, right? In order to identify and sustain improvement opportunities, monitor process performance and adherence as real-time as pragmatically possible, and synchronize processes with customer demand, lean practitioners must apply time-based lean math. The basic sub-categories are takt time, cycle time, processing time, lead time, and pitch. Within each sub-category there are a host of other math considerations. For example within the category of cycle time, we should understand machine cycle time, effective machine cycle time, operator cycle time, planned cycle time, and weighted average cycle time.

“iIities.” This is a catch-all for such categories as availability, capability, reliability, stability, and quality (OK, we know that quality ends in “ality.”). As you can well imagine there is a tremendous amount of math around these categories, including operational availability, operating rate, overall equipment effectiveness, mean time between failure…

Work. The real title of this category should be, “Load, Capacity, Productivity, and Efficiency,” but it’s too darn long for the menu or sidebar! Here, the focus is on characterizing work for, and within, a given system. This stuff helps provide insight into how effectively resources process their work. Posts will address things like optimal staffing, work content variation, min/max cut theorem, and process cycle efficiency.

Inventory. This category is actually about and inventory AND replenishment. Certainly, excess inventory is waste. However, inventory is typically needed somewhere within the value stream. It’s part of a value stream’s circulatory system. Implicit in Little’s Law is the notion that if there is no inventory, there is no throughput. The lean practitioner should have a basic understanding of math around inventory (standard work-in-process, Little’s Law, etc.), inventory management (inventory turns, days of inventory on hand, etc.), every part every interval, and pull system math (the various kanban sizing formulas and related elements, triggers, reorder point, and FIFO lane sizing).

Metrics. The basic True North performance metric categories are human resource development, quality improvement, delivery/lead time/flow improvement, cost/productivity improvement. This can be simplified as people, quality, delivery, and cost and matches well with Shigeo Shingo’s four objectives of improvement – make things easier, better, faster, and cheaper. This Lean Math^TM category will address the related operational and (some) financial-oriented performance metrics.

Basic Math. Actually, this is basic math AND hypothesis testing. This category will cover the bread and butter techniques for describing and comparing datasets. Posts within this category will ultimately cover simple math like average and median, as well as more advanced math like standard deviation, hypothesis testing, t-tests, and linear regression.

Measurement. Really, measurement AND experimentation. Lean, in many ways, is measure-improve-measure and PDCA is certainly founded upon experimentation. Here, we will look at the math around gauge R&R studies, sampling, components of variation, and design of experiments.

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Blog

"Lean Math: Figuring to Improve" Receives 2017 Shingo Publication Award

Setup Reduction Strategy and Internal versus External Changeover Time

Changeover Time

Benchmarking and the Absolute Benchmarking Process Efficiency Ratio

New Book, New Look, and New Content

Inventory Record Accuracy

Pages

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"Lean Math: Figuring to Improve"...

Setup Reduction Strategy and Internal versus...