"Lean Math." Now, there's a name that evokes passion in the heart of every lean practitioner!?
But, the truth is effective lean transformations require some level of math, whether it's the often deceptively simple calculation of takt time, sizing kanbans, calculating process capability, or anything in between. It's hard to get away from math-free lean and certainly math-free six sigma!
Lean Math is not intended to be some purely academic study and it does not pretend to be part of the heart and soul of lean principles. Rather, it's a tool and a construct for thinking. Here we want to integrate lean math theories and examples with experimentation and application.
In the end, we hope the blog, along with its fledgling community, lives up to the tag line, "Figuring to improve."
Blocking, not to be confused with the type that exposes one to the risk of physical injury, is a REALLY clever way to run experiments.
Blocking can be thought of as grouping experimental runs. And when experimental trials are grouped, interesting things can happen - not the least of which is you can really increase your signal to noise ratio.
Consider the following operational life data from Company ABC:
The process capacity sheet, also known as a table of production capacity by process or production capacity chart or process capacity table, is one of the three basic tools for establishing a standard operation. The other tools are the standard work combination sheet and standard work sheet. All three standard operations sheets are populated with data obtained through direct observation (as is the time observation form).
From my experience, there are a handful of pull system design steps. This post seeks to "simply" outline those steps and some of the math that should be considered.
However, don't let the brevity of this post mislead you. It isn't necessarily simple.
We will address more and more of the referenced math through future Lean Math posts.
The time observation form, also known as a process study form, is a basic and often-used tool for lean practitioners. Note that here we are talking about the application of the continuous time observation method and not the work sampling method.
The form, in combination with a stop watch, serves multiple purposes, including:
The VMA's were outrageous?!?
Well, if the media is to be believed, the news of the day was that it was an outrageous Video Music Award show.
Not true and true. Yes - the show was outrageous, no – it wasn’t news.
Let me explain. News is noteworthy, significant, and new. It changes your perspective, it is unusual.
Lean practitioners must properly identify product families in order to value stream map a given family’s flow of material and information. That’s very important, but not always simple.
In order to illustrate how to identify product families and thus value streams, consider the following example. Three different patient groups go to a hospital. The treatment for patient groups 1 and 2 consists of three steps A, B, and C. However, the treatment for patient group 3 consists of only step D.
Work content (Wc) represents total operator cycle time or, if multiple operators, the sum of operator cycle times to perform a specific process(es) or sub-process(es). The scope of human work, including both value-added and non value–added activities, may encompass a complete value stream or only a portion of it. For example, the lean practitioner may speak of the work content to check-in and room a patient, assemble a sensor module or process a claim.
A complex man, born July 30, 1863, Henry Ford developed the automotive mass production assembly line. His relentless and systematic focus on efficiency and costs reduction resulted in many tec
When evaluating countermeasures, it is common to determine which countermeasure has the best average result. A lazy analyst may then conclude that the countermeasure with the overall best average is the preferred solution. On many occasions this intellectual sloth may result in the best choice, but there are some occasions where this type of thinking could result in disaster.
The wrongheaded thinking arises from not realizing that just because the average result is better; it doesn’t mean that the overall results are better.
