Methodology map: which one fits each problem

In one line

Each methodology was born to solve a different problem, and choosing well starts with knowing which one is yours.

The timeline

Bellon Álvarez walks through the historical sequence of the ways of organizing production, and it works as a backbone:

1. Taylorism: time study, standardization and planning separated from execution.
2. Fordism: those principles on an assembly line, with production in large runs.
3. Toyotism / TPS: flexibility, just in time and jidoka, in response to a market that demands variety.
4. Lean: the Toyota system exported as techniques to eliminate waste.
5. Total quality and Six Sigma: quality as everyone's responsibility and as a problem of measurable variation.
6. Lean Six Sigma and the Theory of Constraints: combinations and prioritization approaches.

What question each one answers

Methodology	Question it answers	Typical tools
Work study (Taylor)	How long should this task take?	Time study, standard time
Lean / TPS	What do we do that does not add value for the customer?	Muda, VSM, 5S, SMED, kanban, jidoka
Just in Time	How do we produce only what is consumed?	Pull, kanban, takt time
Six Sigma	How much variation does the process have and how do we reduce it?	DPMO, sigma level, DMAIC, Cpk
Lean Six Sigma	How do we quickly solve a problem with data?	DMAIC with flow tools
Theory of Constraints	What limit sets the output of the whole system?	Five steps, bottleneck capacity
Total quality (TQM)	How do we get the whole organization to improve quality?	Quality circles, PDCA, ISO 9001
TPM / RCM	How do we keep machines from slowing down the flow?	Autonomous maintenance, OEE, failure analysis

How to choose where to start

This is a practical guide from the site, not a rule from any source: it helps you get oriented, not replace the analysis of your plant.

• A lot of inventory, waiting and long lead times: start with Lean (muda, VSM, kanban).
• Defective parts or results that vary for no reason: Six Sigma or DMAIC, with Pareto and Ishikawa.
• You do not meet deliveries even though the rest of the plant seems to have spare capacity: Theory of Constraints and capacity.
• Long changeovers: SMED.
• Equipment stoppages: TPM and RCM.
• There is no improvement habit or management commitment: total quality and kaizen.
• You do not know where to start: a SWOT of the area organizes the diagnosis.

Real example

The Ciudad Juárez case uses several of these ideas on a single assembly line: Six Sigma to measure (sigma level of 2.6, DPPM of 115,044), Lean to diagnose (takt time of 6 seconds against stations of more than 7), a data-based cause analysis that ruled out two hypotheses and confirmed line balancing, and a control plan. In 24 days the sigma level rose to 3.4 and shipment compliance reached 100%. Neither of the two "schools" would have solved the problem alone: Lean showed where the imbalance was and Six Sigma made it possible to verify that it was the dominant cause.

Niebel and Freivalds sum it up from history: the Toyota system applied Taylor's scientific management and Ford's line with a broader scope, and today we call it lean manufacturing. In other words, there is no break: each methodology incorporates the previous one.

Common mistakes when choosing

• Importing tools without the system: implementing kanban without quick changeovers or stable quality ends in shortages.
• Applying everything at once: the Icesi University paper warns that Lean techniques should not be applied haphazardly, because each one contributes a specific lesson.
• Confusing the name with the result: a plant can say it does Lean without ever having measured a lead time.

In summary

Methodologies are layers, not rivals. The order that usually works is: diagnose (SWOT, VSM, capacity), attack the constraint or the dominant waste, measure with data (Six Sigma, DMAIC) and sustain with standards and an improvement culture.