Applied Six Sigma in Elegant Reasonism
DMAIC
DMAIC, pronounced duh-may-ick, focuses on incrementally improving existing processes. It is the most widely known methodology and the one most associated with Six Sigma. Here’s a breakdown of the acronym:
D: Define investigation (e.g. customer) needs, requirements, and project goals.
M: Measure the key aspects of the current process. According to McAdams, “This is when you start to understand your process and collect data on it.”
A: Analyze data. “You really dig into what types of errors occur and where they occur so you can target the big ones. It’s always looking at that 80/20 rule. Let’s see if we can find 20 percent of the reasons that give us 80 percent of the defects and let us reduce those,” says McAdams.
I: Improve processes. Test and verify that the improvements work.
C: Control future implementations of the processes to ensure that errors don’t creep in again.
Define
Defining the investigation is critical. Not only are the outcomes or outputs identified but how the various demographic groups think about those results are quantified. We strongly encourage the use of the ISO 9001 Unification Tool across: Recognition, Illumination, and Analysis phases, but especially as early as possible between the investigation leadership and any stakeholders, sponsors, etc. (e.g. management). The tool will help those charged with development of the treatise ultimately assure the integrity of the final Treatise.
Elegant Reasonism requires employing a plurality of models and so different stakeholders will hold differing definitions for concepts and investigators need to understand that those definitions may very likely be mode shifted out from under the stakeholders, sponsors, and management. This is why it is important to document everyone’s position and definitions before the investigation begins. As it happens this is also a requirement for Bayesian analysis integrated in the holistic process as well. So this is not an idle exercise.
Measure
Measurement of existing processes is: 1) likely entrenched in M1 thinking, 2) going to require enabling mode shifted views, 3) require establishment of new metrics in alignment with the real unified Universe (which does not happen until after #2 is completed). Measurement is not accomplished until metrics are employed. Many projects sponsored by the National Science Foundation establish ‘sigma values’, but those have historically been developed using M1 based metrics. That’s a problem.
Implications of M1 based Metrics
What’s the big deal if metrics are based on M1? It should be superficially obvious that implies then that the associated sigma values are associated with an EIM that does not close to unification. However, and using QMS root cause procedures, so what? Well, what is not so obvious is that means what constitutes a ‘sigma defect’ is completely out of alignment. It means that there are issues constituting sigma defects that are being completely ignored and overlooked. All the reasons M1 fails to close to unification are several examples, but more importantly they may also represent direct sigma defects in the body of work under investigation. It also means that the sigma value reported earlier may be considerably higher than the actual real sigma value that would otherwise be reported by Elegant Reasonism for exactly these reasons.
Employment of Compartmentalized Sigma Ratios re: LEEs
Beware high Sigma Ratios tied out to EIMs which can not close to unification. Such claims significantly obfuscate the real realtionships being measured relative to the precipice of those same measurements in context of the unified Universe. Such claims are in and of themselves Sigma Defects made manifest through thinking which can not successfully navigate the Process Decision Checkpoint Flowchart.
Analyze
The analysis of Six Sigma within an Elegant Reasonism framework takes place recursively and employs Root Cause Analysis primarily in the Illumination phase but to some degree in every step and stage of the three phases: Recognition, Illumination, and Analysis. We then must also apply it within the sets associated with an investigation’s ‘domain of discourse’, which necessarily includes the POI/N Statistical Analysis and each of the EIMs representing the plurality of EIMs employed by the team. What is not necessarily obvious here is that Six Sigma is also being applied to the other analytical layers as well as those associated primarily with the investigation. This is required because of the many paradigm shifts that occur mode shifting paradigms of interest model to model and the associated belief systems associated with old ways of thinking vs new ways of thinking which must then be articulated in a Bayesian framework. Installing these various metrics and conducting the associated analysis is the mission of the Six Sigma Analysis Layer within Translation Matrices.
Improve
While the normal improvement metrics apply normally associated with application of Six Sigma within an enterprise, Elegant Reasonism brings an entirely new dynamic to the mission. Mode shifting current thinking to new thinking is obvious. Not so obvious are the plethora of systemic details and how those details relate to the business processes of the enterprise. And then there are the belief systems of the employees dealing with all of this when the investigation teams are finished.
Control
Given where civilization is at the moment the control mechanisms are still likely out in the future somewhere. Suffice it to say though that there will be many aspects of Elegant Reasonism employed and Six Sigma will be right there at ever step and stage.
Improve
Given where civilization is at the moment the control mechanisms are still likely out in the future somewhere. Suffice it to say though that there will be many aspects of Elegant Reasonism employed and Six Sigma will be right there at ever step and stage.
DMADV
DMADV, pronounced duh-mad-v, focuses on optimizing new products or processes to Six Sigma standards. The acronym breaks down like this:
D: Define the investigation (e.g. customer) or company goals.
M: Measure CTQs (characteristics that are Critical To Quality), measure product capabilities, production process capability, and risks.
A: Analyze data from your measurements as a function of your metrics.
D: Design the new process based on the analysis in the previous step.
V: Verify the design through a pilot run, implement the new process, and hand off to the process owner.
Define
Defining the investigation is critical. Not only are the outcomes or outputs identified but how the various demographic groups think about those results are quantified. We strongly encourage the use of the ISO 9001 Unification Tool across: Recognition, Illumination, and Analysis phases, but especially as early as possible between the investigation leadership and any stakeholders, sponsors, etc. (e.g. management). The tool will help those charged with development of the treatise ultimately assure the integrity of the final Treatise.
Elegant Reasonism requires employing a plurality of models and so different stakeholders will hold differing definitions for concepts and investigators need to understand that those definitions may very likely be mode shifted out from under the stakeholders, sponsors, and management. This is why it is important to document everyone’s position and definitions before the investigation begins. As it happens this is also a requirement for Bayesian analysis integrated in the holistic process as well. So this is not an idle exercise.
Measure
Same discussion as above. Remember that many of the metrics will need to be mode shifted by the investigative team before they can be implemented for measurement.
Analyze
Same discussion as above and caveats as with measurements.
Design
The design will need to integrate aspects of Six Sigma that are net new insights based on the Treatise ultimately developed and this is a new aspect of Six Sigma. These issues will likely find their way into the Treatise as it is developed. Having said this it is important to remember distinctions between M5 and M1 thinking that may produce net new insights in design of metrics, experiments, processes, and materials which have never been thought of by anyone. Those insights, as a function of the patent license, flow back to SolREI for incorporation on this website for everyone as appropriate.
Verify
Given where civilization is at the moment the control mechanisms are still likely out in the future somewhere. Suffice it to say though that there will be many aspects of Elegant Reasonism employed and Six Sigma will be right there at ever step and stage.
Six Sigma Metrics
There are many Six Sigma metrics and/or measures of performance used by Six Sigma practitioners. Sigma level, Cp, Cpk, Pp, Ppk, takt time, cycle time, utilization etc, will be covered elsewhere. Remember that unification demands established relationships between higher ordered and lower ordered constructs. Evidence chain patterns should reflect these relationships across the entanglement gradient for both emergent and convergent points of view and do so consistently no matter how restful and they should mode shift effectively. A few Six Sigma metrics are:
- Defects per Unit (DPU)
- Defects per Million Opportunities (DPMO)
- Yield (Y)
- Rolled Throughput Yield (RTY)
Before we dive into the metrics themselves we must touch on the concept of “metrics”. All projects or programs have purposes and those purposes must be measurable to be effectively managed. Six Sigma uses the transfer function as an approach to achieving improvements. That approach mandates the need for a measurable primary metric and suggests secondary metrics. Learning from the entanglement gradient we realize that scale matters but does not eliminate the requirement to integrate systemic thinking relative to emergence and convergence issues. That learning point applies equally to metrics and remember, they too must mode shift effectively and that means successful navigation of the Process Decision Checkpoint Flowchart. So what is a primary metric?
Primary Metrics
The primary metric is a generic term for a Six Sigma project’s most important measure of success and it must successfully navigate Elegant Reasonism, its processes & methods, rules, meet requirements from across the realm of c’s and those demanded by unification itself. It means that evidence chain patterns are effectively mode shifted EIM to EIM, no matter how restful, such that POI/Ns are rendered across the realm of c’s to full illumination and illustration in context of the unified Universe. The Primary metric is defined by the Black Belt, GB, MBB or Champion. A primary metric is an absolute MUST! For any project and it should not be taken lightly. Here are a few characteristics of good primary metrics:
- Primary metrics should be tied to the problem statement
- Primary metrics should be measurable
- Primary metrics should be expressed with an equation
- Primary metrics should be aligned to business objectives
- Primary metrics should tracked at the proper frequency (hourly, daily, weekly, monthly etc.)
- Primary metrics should be expressed pictorially over time with a run chart, time series or control chart
- Primary metrics should be validated with an MSA
The primary metric is the reason for your work, it’s the success indicator and beacon for your project. The primary metric is of utmost importance and is the focus of your project BUT…not at the expense of your secondary metric.
Secondary Metrics
The secondary metric is the thing you don’t want sacrificed on behalf of a primary improvement. A secondary metric is one that makes sure problems are not just “changing forms” or “moving around”. The secondary metric keeps us honest and ensures we’re not sacrificing too much for our primary metric. If your Primary Metric is a cost or speed metric then your Secondary Metric should probably be some quality measure. Remember that generally higher ordered constructs infer lower ordered constructs where as lower ordered constructs may directly illuminate their higher ordered parents. Using atoms as an example because commonly atoms known. To illuminate small objects we generally employ constituents of atoms (e.g. electrons) in electronic microscopes to discern very small features exactly because they are smaller. Below these scales however we run into issues because of our technological maturity circa 2021. That features are not discernible at lower levels is more a statement of that maturity than it is of their existence. Consequently we must infer their existence employing Elegant Reasonism.
- Example: If you were accountable for saving energy in an office building and your primary metric was energy consumption then you could shut off all the lights and the HVAC system and save tons of energy…..except that your secondary metric(s) are probably comfort and functionality of the work environment.
Primary and Secondary Metrics are simply guideposts for your Six Sigma project. They can be one of many measures that are important to the business (sales, throughput, time, speed, weight, length, velocity, accuracy etc. Let’s now turn our attention to a few common Six Sigma type metrics starting with Defects per Unit.
Defects per Unit: DPU
DPU stands for “Defects per Unit”. DPU is the basis for calculating DPMO (Defects per Million Opportunities) and RTY (Rolled Throughput Yield) which we’ll cover below. DPU is found by dividing total defects by total units:
- DPU = D/U
For example if you have a process step that produces an average of 65 defects for every 598 units then your DPU = 65/598 = 0.109 (10.9%). Another way of referring to DPU would be calling it a ‘defect rate’. What might your defect rate be if you counted 34 defects out of 212 units sampled? if you answered 16% you would be correct.
The 5S Approach
The 5S idea of Separate or Sort (Seiri), Straighten (Seiton), Shine (Seiso), Standardize (Seiketsu), and Sustain (Shitsuke), in no particular order can be used to teach general concepts to groups and is often associated with Six Sigma. Our experience encountering this is more in classroom settings more than in general practice. Program effectiveness based on these ideas is dependent on applicability to the specific set of circumstances, which in and of itself might be problematic. Still the approach does help some classify issues to be tackled in context.
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