Research libraryMeasure Before You Model
Chapter 12 of 14 · Part III · Draft web edition
A corrective-action system should distinguish abnormal variation, test causes, verify effects and update standard work rather than count completed actions.
The cloth is woven from this chapter's 5 exhibits: each weft is one exhibit's own data, normalised; each warp group is a section. The probe reads the exhibit's own value where it crosses. Procedural visualisation, not a measurement.
Read-out
Derived GFT workflow sequence. S05 supports baseline gap identification and KPI change measurement, S09 supports statistical comparison with prior process behaviour, S41 supports inspectable A3 logic and reverse follow-up, and S43 supports benefit monitoring beyond intervention completion. No factory operating effect is asserted.
Unit: . Status: derived. Sources: S05, S09, S41, S43.
An operational improvement closes only when two propositions survive empirical inspection: first, that discriminating evidence supports the selected root cause against competing explanations, and second, that a comparable production population demonstrates the expected gain without degrading a safety, quality, delivery or working-time guardrail.[S02][S41][S43] Completing an action item, holding a briefing, replacing a sewing attachment or issuing a revised form is an administrative output, not a verified operating result.[S08][S43] In GFT's performance-management architecture for a greenfield cut, make, trim and finishing plant, corrective action forms a closed engineering loop linking a measured baseline gap through variation checks, competing causal hypotheses, controlled trials and post-completion benefit audits to released standard work.[S05][S09][S41][S43] Where any link in that chain remains untested, the item stays open in the governance register regardless of whether a scheduled completion date has passed.[S22][S43]
This distinction between activity completion and verified effect determines whether the management cadence in Chapter 11 compounds learning or recycles tasks. Reviews of Overall Equipment Effectiveness (OEE) implementations highlight a lack of systematic frameworks that translate loss measurement into sustained improvement steps.[S08] In garment factories, that gap often appears as action-log theatre: huddles and reviews generate task lists, supervisors mark tasks complete once a mechanic adjusts a machine or a trainer speaks to an operator, and the same defects or delays return weeks later.[S04][S08][S41] In Cameroon, where as of the 31 January 2024 programme cut-off about 95 percent of cotton fibre is exported raw against about 5 percent processed locally, and where policy targets 50 percent local processing by 2030, a new plant cannot waste engineering capacity on unverified fixes.[R06][R07] Ramp-up research shows that a new process starts poorly understood, with low yields and rates while teams learn the work.[S11] Treating unverified adjustments as closed improvements corrupts institutional memory and pollutes the dataset needed before predictive models are considered at later maturity gates.[S11][S27]
Exhibit 55 defines the seven-stage verification sequence embedded in the factory's system of record. Rather than moving linearly from a report to a closed ticket, the loop places gates after variation analysis, hypothesis testing, countermeasure execution and standardisation.[S05][S09][S41][S43] When a trial fails to move the primary indicator or breaches a guardrail, the workflow routes the team back to competing causal evidence.[S41][S1206]
Exhibit 55 establishes that standardisation follows result verification, and final closure follows a sustained-effect audit across later shifts.[S41][S43] What Exhibit 55 cannot establish by itself is whether the data entering the first node are accurate, whether the sample size can detect the shift, or whether supervisors possess the coaching skill to maintain the revised method; those requirements are enforced through the measurement, statistical and training controls below.[S14][S24][S40]
12.1
Read-out · illustrative
Illustrative: GFT hour-by-hour line-board layout for one 8-hour sewing shift (40 operators, 24.0 SMV woven trouser, ramp cohort week 4 at 65 percent target efficiency). Values are illustrative design entries showing how balanced in-process and end-of-process measures (S02), daily line balancing (S04) and unmerged downtime causes (S07) appear with an explicit owner and response window. Not an observed GFT factory result.
Unit: illustrative shift-board control blocks. Status: illustrative. Sources: S02, S04, S07. Illustrative figures are teaching examples, not measured factory results.
Read this exhibit in chapter 11 ↗The first decision in a corrective-action system is not which diagram to draw, but which gap merits scarce engineering, maintenance and supervisory time.[S05][S22] In the International Labour Organization's (ILO) Sustaining Competitive and Responsible Enterprises (SCORE) programme in Ethiopia's garment sector, improvement begins at step zero with a baseline assessment to identify gaps and opportunities, and tracks change through Key Performance Indicators (KPIs).[S05] GFT applies this baseline-first rule at the boundary where loss occurs.[S01][S05] A valid charter specifies the line, station or operation code, style or family, method revision, window and metric contract from Chapter 4, retaining both numerator and denominator behind every rate.[S01][S03][S1203]
An actionable problem statement describes an observable deficit in a governed record rather than a wish for better performance or a premature guess at the cure.[S01][S41] Stating that first-pass yield at end-of-line inspection on a woven-shirt cohort fell below its threshold across five shifts, with most nonconformities coded to collar-topstitch puckering at a named operation, gives the team a clear starting point.[S06][S10][S1203] Stating that quality is poor or that operators need retraining fails to locate the loss boundary and embeds an untested assumption inside the definition.[S41]
To serve as a baseline, the historical record must represent a defined population rather than a single shift tile.[S05][S09] It retains the source rows, inclusion rules, boundary and data-quality qualifications behind the indicator.[S23][S24] During ramp-up, when the process is poorly understood and yields move as operators learn, the cohort stays narrow enough to avoid pooling early learning shifts with stabilised work.[S11] During steady runs, a multi-week window gives a stronger estimate of variation.[S09][S1207] Before approval, the data steward confirms that an apparent drop was not created by a routing change, modified bundle count or revised defect rule.[S22][S25][S40]
A greenfield plant generates more variances than its engineers can investigate at once. Left to informal choice, teams pick whichever metrics are easiest to chart rather than the losses constraining factory survival.[S02][S22] Garment lean guidance calls for balancing financial, behavioural and core-process metrics while combining in-process and end-of-process indicators.[S02] GFT translates that balance into a triage filter across its six KPI families:
Before authorising a project, the weekly chair asks four questions.[S08][S22] Is the gap material to a strategic outcome or an immediate safety duty?[S02][S18] Is the baseline population bounded, complete and free of measurement distortion?[S24][S40] Does an accountable role hold authority to change the candidate method, machine, material or staffing condition?[S22] Can the primary indicator and its guardrails be observed within a reviewable window?[S02][S43] If any answer is no, the first task is repairing the definition or measurement contract.[S24][S40]
12.4
Read-out
Illustrative binomial p-chart for n = 200 inspected garments per shift across 10 shifts, applying S09 and S0602. Baseline mean p = 6.0 percent; 3-sigma UCL = 11.04 percent. Customer specification (4.0 percent) is shown separately to distinguish chronic capability gaps (Shifts 1 to 7, 9 to 10) from assignable-cause spikes (Shift 8 at 12.5 percent, triggering OCAP per S0604).
Unit: percent nonconforming (n = 200). Status: illustrative. Sources: S09, S0602, S0604. Illustrative figures are teaching examples, not measured factory results.
Read this exhibit in its chapter ↗12.4 · Introduction
Once a measurable gap is confirmed, the team must characterise the variation behind it before intervening on the line.
Exhibit 29, chapter 06: S1
12.5 · Control limits, customer specifications and management targets serve distinct decisions
A frequent error in factory reporting is plotting a customer tolerance or management target on a chart and treating every shift below that line as an assignable event.
Exhibit 29, chapter 06: S1
12.6 · Attribute charts and supplementary run rules require sample-size and false-alarm discipline
Because garment logs track the fraction of nonconforming garments across bundles or shifts, teams use attribute proportion charts ($p$-charts).
Exhibit 29, chapter 06: S2
12.4 · the bodyThe film above follows these sub-steps.
Once a measurable gap is confirmed, the team must characterise the variation behind it before intervening on the line.[S09][S1201] NIST's statistical process control (SPC) guidance states that process control compares what is happening today with what happened previously, using historical data to establish stable process behaviour.[S09] Separating chance (common-cause) variation built into the system from assignable (special-cause) variation triggered by a specific disturbance prevents two costly mistakes: tampering with a stable station after routine random movement, or treating a sudden machine or material fault as if it required a plant-wide retraining campaign.[S09][S1201]
Keeping these boundaries distinct guides action.[S09][S1207] When a shift's defect rate or cycle time breaches a control limit, NIST guidance states that the process is probably out of control and warrants investigation to eliminate the assignable cause.[S1201] Typical special causes include a damaged rotary hook, a wrong needle size fitted after a break, an air-pressure drop at a fusing press, or an unshaded fabric roll.[S07][S1202] Out-of-Control Action Plans (OCAPs) detail the diagnostic flowchart and containment procedure followed when a signal occurs.[S1202] Removing a special cause restores the prior baseline; it does not improve that baseline beyond its earlier capability.[S09][S1201]
Conversely, a line can stay inside control limits while first-pass yield sits below target or seam variation exceeds specification.[S1201][S1207] There, no single hour or operator is an outlier; the loss is a common-cause property of work allocation, folder design, lighting, skill drills or material presentation.[S03][S04][S12] Demanding explanations for routine noise inside control limits is tampering. Improving a stable but incapable process requires a system change tested through a controlled trial.[S09][S1207]
Because garment logs track the fraction of nonconforming garments across bundles or shifts, teams use attribute proportion charts ($p$-charts).[S1203] NIST defines the proportion nonconforming as the ratio of nonconforming items ($D$) to total items ($n$), modelled under a binomial distribution with mean $p$ and variance $p(1-p)/n$ when units are independent and the process is stable.[S1203] Two rules follow. First, because limit width depends on $\sqrt{p(1-p)/n}$, comparing shifts with different denominators ($n$) without adjusting limits creates false flags on small shifts.[S1203] Second, when rework loops violate independence or ramp-up learning shifts $p$ daily, classic 3-sigma binomial limits serve only as approximate guides.[S11][S1203]
Engineers must also manage false alarms when choosing signalling rules.[S1201][S1205] Under a normal distribution, 3-sigma limits correspond to a one-sided probability of 0.00135, or 0.0027 in both directions, giving low risk of chasing nonexistent assignable causes.[S1201] NIST notes that a chart is in control only when all points lie within the limits and form a random pattern, since systematic runs (such as 25 of 30 points above the centre line) indicate a shift even inside the limits.[S1201] However, NIST warns that while 3-sigma limits produce a false alarm once every 371 points on average, adding Western Electric Company (WECO) run rules increases false alarms to about once every 91.75 points on average.[S1205] Across dozens of station metrics, false alarms every 91.75 points would swamp engineers.[S1205] GFT reserves supplementary run rules for bottleneck or safety measures and preserves old limits beside any recalculated baseline.[S09][S1205]
12.7
When a gap requires structured problem solving rather than routine OCAP containment, GFT uses the A3 format as an evidence contract.[S41][S1202] Its value lies in making every inference between the observed loss and the revised standard open to challenge.[S41] The Lean Enterprise Institute recommends reading an A3 in reverse, starting from follow-up and standardisation and moving backwards through countermeasures, root causes, target condition and current condition, so owners and leaders confirm a logical, fact-based process.[S41]
Read-out
| 1. Current condition | Dated baseline cohort, boundary and denominator rows | Is the gap reproducible and free of coding breaks? | Data steward |
|---|---|---|---|
| 2. Variation and target | Control chart or run sequence with target mechanism | Does the study match special or common cause behaviour? | Quality or IE lead |
| 3. Root-cause proof | Hypothesis matrix, gauge check and discriminating test | Did evidence eliminate rival explanations? | Investigation owner |
| 4. Countermeasure trial | Pilot release log, affected stations and guardrail list | Was the physical or rule change executed as designed? | Line or maintenance lead |
| 5. Effect verification | Before, after and comparison bridge with audit adjustments | Did net benefit hold without a guardrail deterioration? | Plant review chair |
| 6. Standard and sustain | Method revision, skill sign-off and 30-day sustain check | Can the next shift repeat the gain without extra support? | Operations manager |
Derived GFT governance register combining baseline gap measurement (S05), historical SPC comparison (S09), data-quality fitness (S24), measurement-system error analysis (S40), reverse A3 logic verification (S41) and post-completion benefits monitoring (S43). Contains governance criteria only, not factory operating results.
Unit: . Status: derived. Sources: S05, S09, S24, S40, S41, S43.
Exhibit 56 stops an investigation from jumping from link 1 to link 6 when a supervisor says operators were told to be careful.[S41] Each row requires a recorded artefact and a gate owner before advancing.[S22][S41] What Exhibit 56 cannot do is generate hypotheses or observe the floor; a team can still fill a table with weak claims unless leadership checks the underlying evidence at the weekly review.[S08][S41]
…investigation from jumping from link 1 to link 6 when a supervisor says operators…
S41
Scientific problem solving in a greenfield plant requires keeping negative results.[S11][S41] When an A3 team tests whether needle heating causes thread breakage on heavy twill, measures needle temperature across speeds, and finds breakage unchanged while cone-unwinding tension explains the fault, both the falsified heating test and the confirmed tension test remain in the record.[S23][S41] Deleting rejected hypotheses to make the A3 look tidy destroys half its learning value and forces later teams to repeat dead-end trials.[S11][S25][S41]
Interlude · the cloth half-woven
Woven: sections 12.0 to 12.7Still to weave: 12.10 to 12.19
Read-out
Illustrative worked example. 64 OTIF orders + 16 orders not OTIF = 80 orders due. OTIF rate = 64 / 80 x 100 = 80 percent. These are assumed values used to demonstrate the calculation.
Unit: illustrative orders and percent. Status: illustrative. Illustrative figures are teaching examples, not measured factory results.
Read this exhibit in its chapter ↗12.10
Exhibit 579 paragraphs step it
Read-out
Illustrative diagnostic scoring matrix for a seam-puckering investigation. Scale runs from 0 (contradicted by evidence) to 5 (fully consistent with discriminating test). S07 supports event-level disaggregation, S24 supports data-record checks, S40 supports gauge/observer repeatability studies, and S1208 supports blocked comparison across materials, machines and operators. Scores are illustrative method examples, not GFT factory measurements.
Unit: illustrative evidence consistency score (0 to 5 scale). Status: illustrative. Sources: S07, S24, S40, S1208. Illustrative figures are teaching examples, not measured factory results.
Where discipline is weak, root-cause analysis becomes an opinion poll: one voice blames operator care, the mechanic blames fabric, and the supervisor blames cutting.[S07][S41] GFT replaces anecdote with competing hypotheses across six families: material, method, machine, measurement, staffing and environment.[S03][S24][S40] None is accepted until an observable prediction discriminates between it and its rivals.[S41][S1208]
Before changing a machine, sequence or training plan, the team tests whether the apparent problem is an artefact of measurement or recording.[S24][S40][S1204] NIST's characterisation guidance states that a measurement process is a production process in which measurements are the output, quantified by bias, short-term precision, day-to-day variability and uncertainty.[S1204] NIST's Gauge R&R guidance outlines how to characterise repeatability and reproducibility errors in production instruments.[S40] Alongside this, the UK Government Data Quality Framework defines six core dimensions (completeness, validity, consistency, timeliness, uniqueness and accuracy) for structured records.[S23][S24]
On a garment floor, measurement error comes from digital logs and human grading:
Whenever a signal depends on visual grading, manual counts or meter reads, GFT requires a measurement check inside link 3 of the A3.[S40][S41] Two or three inspectors independently classify an illustrative blind set of 20 to 30 garments twice against the reference sample to verify repeatability and agreement.[S40][S1204] If grading disagreement explains the shift, the countermeasure is calibrating the inspection standard and lighting, not altering the station.[S40][S1204]
Once data and grading stability are confirmed, physical and organisational hypotheses compete through discriminating predictions.[S41][S1208] Because OEE and summary defect logs merge events, high-level KPIs rarely isolate a specific mechanism alone.[S07] Engineers stratify the event log and run short tests where rival hypotheses predict opposite outcomes.[S07][S1208]
On the floor, fabric lots, machines and operators often change together, confounding observation.[S11][S1208] NIST's Design of Experiments (DOE) glossary defines blocking as scheduling treatment combinations so effects from known changes in materials, operators or machines are concentrated in the blocking variable, isolating nuisance effects.[S1208] Blocked trials on a sewing line are fast: two qualified operators sew bundles from Lot A and Lot B on one calibrated machine, or one lot runs across two feed-dog settings while holding operator and method constant.[S03][S1208]
Exhibit 57 shows how a team scores five competing hypotheses against four evidence checks during an illustrative collar-puckering investigation.[S07][S24][S40][S1208]
In Exhibit 57, an illustrative score of 0 means the check contradicts the hypothesis, while 5 means it survives a discriminating test.[S41][S1208] The log check (0 for H2) and blind inspector check (1 for H1) rule out recording and grading errors.[S24][S40] Lot stratification shows the spike concentrated in one interlining lot (5 for H4), and a blocked trial across presser-foot settings confirms that the interlining lot drives the fault while foot pressure acts only as a secondary amplifier (5 for H4, 2 for H3).[S07][S1208] What Exhibit 57 cannot prove alone is sample adequacy; the record must attach the actual bundle counts and test logs.[S1203][S1207]
12.13
A verified cause improves performance only when an accountable role changes the condition producing the loss.[S08][S22] The OEE review's call for systematic improvement steps after measurement is an ownership requirement: action lists stall when tasks sit with committees or supervisors who lack authority to alter engineering or purchasing rules.[S08][S22]
Grounded in data-governance principles enforcing decision rights and accountable roles, GFT assigns countermeasure ownership by authority over the mechanism changed:[S22]
NIST's process-improvement guidance notes that a process seldom has just one desirable output characteristic; several interrelated characteristics exist such that improving one can degrade another, such as rate versus consistency.[S1206] On a garment line, raising speed at one station can increase defects, flood downstream stations, break needles or encourage skipping ergonomic steps.[S02][S10][S18]
Apparel compensation and working-time evidence shows why behavioural and health guardrails are essential.[S16][S17][S18] While higher base pay led workers in one apparel study to focus on reducing defects and tardiness, Better Work research found partial piece-rate pay associated with poorer emotional and physical health than hourly pay, and showed that excessive overtime leads to poorer health, reduced efficiency, accidents and turnover.[S16][S17][S18] GFT prohibits counting any countermeasure as a verified improvement if its gain came from extending hours beyond the legal and programme guardrail (such as Cameroon's 40-hour standard week, 48-hour maximum and 1.2 overtime rate in the inherited register), increasing strain or hiding rework.[R16][S10][S18]
12.16
B1
B1: Pilot line 82.4, Comparison line 80.5 (illustrative percent first-pass good) · illustrative
Once a trial finishes its window, the action log moves from implementation to verification.
B2
B2: Pilot line 81.8, Comparison line 80.2 (illustrative percent first-pass good) · illustrative
B3
B3: Pilot line 82.2, Comparison line 79.8 (illustrative percent first-pass good) · illustrative
V1
V1: Pilot line 84, Comparison line 81 (illustrative percent first-pass good) · illustrative
V2
V2: Pilot line 87, Comparison line 82 (illustrative percent first-pass good) · illustrative
V3
V3: Pilot line 88, Comparison line 82 (illustrative percent first-pass good) · illustrative
V4
V4: Pilot line 89, Comparison line 83 (illustrative percent first-pass good) · illustrative
The method behind it: Worked example: separate movement from verified benefit.
Illustrative verification model across four baseline windows (B1 to B4) and four post-countermeasure windows (V1 to V4). Pilot line values are 82.4, 81.8, 82.2, 82.0, 84.0, 87.0, 88.0 and 89.0 percent. Comparison line values are 80.5, 80.2, 79.8, 80.0, 81.0, 82.0, 82.0 and 83.0 percent. S09 supports comparison against historical process behaviour and S43 supports post-completion benefit monitoring and attribution analysis. Values are illustrative and do not represent a GFT factory result.
Unit: illustrative percent first-pass good. Status: illustrative. Sources: S09, S43. Illustrative figures are teaching examples, not measured factory results.
12.16 · the bodyExhibit 58 above; its figures are illustrative where marked.
Once a trial finishes its window, the action log moves from implementation to verification.[S41][S43] The UK Department for Transport's Benefits Management and Evaluation Framework requires benefits to be managed and monitored beyond project completion and separates baseline tracking from evaluating attribution.[S43] GFT applies this rule on the floor: installing a guide or rebalancing a line is completion, whereas proving net improvement in first-pass yield or output is benefit realisation.[S08][S43]
During ramp-up, a simple before-and-after comparison on one line is easily confounded by operator learning curves or changing style complexity.[S03][S11][S43] To separate the countermeasure's effect from shared plant trends, GFT pairs the pilot line's before-and-after record with a matched comparison line or blocked cohort running the same style family over the same calendar intervals.[S09][S43][S1208] Exhibit 58 shows an illustrative eight-interval sequence across four baseline windows (B1 to B4) and four verification windows (V1 to V4).[S09][S43]
In Exhibit 58, both lines run parallel during B1 to B4 near 82.0 percent and 80.0 percent.[S09] After the intervention between B4 and V1, the illustrative pilot rises from 82.0 percent to 89.0 percent (a 7.0-point gross move), while the untreated comparison line rises from 80.0 percent to 83.0 percent (a 3.0-point move from shared learning).[S11][S43] Deducting the 3.0-point shared trend leaves an illustrative 4.0-point difference-in-differences contrast before audit corrections.[S43] What Exhibit 58 cannot prove alone is identical style or grading discipline across V1 to V4; analysts must still check the inspection and routing logs.[S24][S40]
Exhibit 59 displays this reconciliation as a waterfall bridge so leadership sees both raw movement and attribution deductions.[S24][S43]
Exhibit 59 prevents claiming 4,200 saved minutes when half occurred on untreated lines and part came from unlogged tickets.[S24][S43] What Exhibit 59 cannot establish alone is whether 2,100 freed minutes reduced cash payroll or increased sales; that requires the cost rules below.[S03][S42]
Exhibit 59 prevents claiming 4,200 saved minutes when half occurred on untreated lines and…
S24, S43
Verification separates physical capacity release from cash savings.[S02][S43] Saving an illustrative 2,100 rework minutes (35 standard hours) does not automatically cut the monthly wage bill if operators are paid on fixed monthly contracts (such as above Cameroon's SMIG of XAF 43,969 a month from 23 February 2024 in the inherited register).[R14][S03] Real economic benefit takes three verifiable forms:
12.19
The final A3 link connects the standard to the daily and weekly cadence in Chapter 11.[S41][S44] Each revised standard carries an updated control plan and OCAP specifying the leading parameter checked at shift start, the lagging KPI on the line board, the owner and the containment trigger.[S02][S1202]
Following benefits-management rules requiring monitoring beyond completion, GFT places newly standardised actions into a 30-day sustain window.[S41][S43] Only when the weekly review confirms at the end of that window that the method remains in use, the net gain holds without special support, and no guardrail has degraded is the item marked closed and verified.[S18][S41][S43] Failed trials are archived with their boundary conditions rather than erased, turning every investigation into reusable evidence for the maturity gates in Chapter 13.[S11][S27][S41]
Check the record
Every knot is a source this chapter cites; select one to read its record, or filter the register by grade. Publication dates and inherited-source limits stay explicit. Read the paper's full evidence summary.
44 sources · 375 citation marks on this pageMost cited: S41, 40 times
Grade AGrade BGrade CKnot size: citations on this page
All 44 records shown
R06 · Grade C · inherited record
Inherited evidence R06
About 95 percent of cotton fibre exported raw against 5 percent processed locally; industrialisation target of 50 percent local processing.
Publication date unrecorded. Inherited source-text record. The original publication has not been independently reopened for this web edition.
R07 · Grade C · inherited record
Inherited evidence R07
SND30 restates the 50 percent local-processing target by 2030.
Publication date unrecorded. Inherited source-text record. The original publication has not been independently reopened for this web edition.
R14 · Grade C · inherited record
Inherited evidence R14
Cameroon minimum wage (SMIG) XAF 41,875 a month in 2023, raised to XAF 43,969 a month from 23 February 2024, about US$76, a rise of 5 percent.
Publication date unrecorded. Inherited source-text record. The original publication has not been independently reopened for this web edition.
R16 · Grade C · inherited record
Inherited evidence R16
Informal share of employment about 90 percent; standard 40-hour week, 48-hour maximum, overtime at 1.2 times.
Publication date unrecorded. Inherited source-text record. The original publication has not been independently reopened for this web edition.
R29 · Grade C · inherited record
Inherited evidence R29
Manual defect inspection 60 to 70 percent accurate, missing 20 to 30 percent of defects; computer vision above 90 percent across more than 40 defect types; line-scan inspection up to 60 metres a minute.
Publication date unrecorded. Inherited source-text record. The original publication has not been independently reopened for this web edition.
c12-S01 · Grade A
ISO 22400-2:2014 Automation systems and integration: Key performance indicators (KPIs) for manufacturing operations management, Part 2: Definitions and descriptions
The KPIs are presented by means of their formula and corresponding elements, their time behaviour, their unit/dimension and other characteristics.
2014. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S02 · Grade A
Lean Manufacturing Techniques for Ready Made Garments Industry
The best approach is to balance the metrics you use among the three categories (financial, behavioral, and core-process) and to use a mix of in-process and end-of-process metrics.
2017. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S03 · Grade A
Sector systems analysis of textiles and clothing subsector in Ghana
A particularly important calculation is the Standard Minute Value (SMV), which is defined as "the time value arrived at for a task based on the average rate of output which qualified workers will naturally achieve without over exertion provided that they know and adhere to the specified method and provided that they are motivated to apply themselves to their work."
2023. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S04 · Grade A
Implementation of the Factory Improvement Toolset in the Asian garment sector: Final report
Line balancing is done by line supervisors systematically, before production through planning, and during production, daily.
2023. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S05 · Grade A
Advancing productivity, quality improvement and decent work in Ethiopia's garment industry: results so far
As step zero, SCORE trainers conduct a baseline assessment to identify existing gaps and opportunities for improvement in SMEs, and measure change through Key Performance Indicators (KPIs).
2022-06-01. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S06 · Grade B
Comparison of OEE-Based Manufacturing Productivity Metrics
The OEE measurement aims to detect production losses and maximise equipment effectiveness.
2023. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S07 · Grade B
Uncovering the Influence of Operational Factors on Manufacturing Efficiency with Real Time Data
However, this loss categorization merges all downtime events, which can obstruct the identification of specific losses, representing a significant limitation of OEE.
2025. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S08 · Grade B
Overall equipment effectiveness: a review and development of an integrated improvement framework
The review found that there is a lack of improvement frameworks with systematic steps specifically developed for OEE implementation.
2020-05-11. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S09 · Grade A
e-Handbook of Statistical Methods: What are Process Control Techniques?
The underlying concept of statistical process control is based on a comparison of what is happening today with what happened previously.
2003. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S10 · Grade A
First Pass Yield Improvement Creates Dramatic Reduction in Lead Time
In addition, total processing time went from 11.8 hours to 3.4 hours and first pass yield jumped from 10% to 90%.
2022-08-04. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S11 · Grade B
Learning and process improvement during production ramp-up
During that time, the new production process is ill understood, which causes low yields and low production rates.
2001. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S12 · Grade B
Evaluation of Manual Skill Degradation Due to Automation in Apparel Manufacturing
Therefore, capacity development drills of sewing operators are essential to maintain an efficient required skill set.
2021-11-23. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S13 · Grade A
Supervisory Skills Training in the Cambodian Garment Industry: A Randomized Impact Evaluation
The study showed that the training improved workers' perceptions of relationships with their supervisors and led to moderate improvements in overall firm productivity.
2009. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S14 · Grade A
Creating Better Jobs for Women and Boosting Productivity in Bangladesh's Garment Factories: An Assessment of the Gender Equality and Returns Program
After completing classroom sessions, trainees continued to shadow a supervisor on a production line for another six to eight weeks.
2025. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S16 · Grade B
Factory benefits to paying workers more: The critical role of compensation systems in apparel manufacturing
Workers focused their increased effort on reducing quality defects and tardiness, two behaviors which individual workers largely control.
2020-02-05. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S17 · Grade A
Piece rate pay brings mixed results for garment workers, new study shows
The research found that workers whose pay is jointly determined by hourly pay and a piece rate (described as partial piece rate pay) are more likely to report reduced emotional and physical health compared to workers paid by the hour.
2018-12-20. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S18 · Grade A
Excessive Overtime, Workers and Productivity: Evidence and Implications for Better Work
It has been shown that excessive overtime can lead to poorer worker health, reduced efficiency, high rates of accidents, and worker dissatisfaction, resulting in high worker turnover.
2011. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S21 · Grade A
NIST IR 8107: Current Standards Landscape for Smart Manufacturing Systems
The ability of disparate systems, however, to exchange, understand, and exploit product, production, and business data rests critically on information standards.
2016. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S22 · Grade A
Data Governance Playbook
Data governance is the process of setting and enforcing priorities for managing and using data as a strategic asset.
2020. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S23 · Grade A
ISO/IEC 25012:2008 Software engineering: Software product Quality Requirements and Evaluation (SQuaRE): Data quality model
This International Standard defines a general data quality model for data retained in a structured format within a computer system.
2008. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S24 · Grade A
The Government Data Quality Framework
There are six core data quality dimensions, as defined by DAMA UK.
2020-12-03. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S25 · Grade A
Data on the Web Best Practices
Finally, to promote the interoperability among datasets it is important to adopt data vocabularies and standards.
2017-01-31. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S27 · Grade B
Rules of Machine Learning: Best Practices for ML Engineering
If machine learning is not absolutely required for your product, don't use it until you have data.
2025-08-25. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S30 · Grade A
The Greenhouse Gas Protocol: A Corporate Accounting and Reporting Standard, Revised Edition
Account for and report on all GHG emission sources and activities within the chosen inventory boundary.
2004. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S36 · Grade A
RECP Experiences at INCALSA
The relative indicators provide a measurement of changes in resource use/pollution in relation to production output.
2015. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S40 · Grade A
e-Handbook of Statistical Methods: Gauge R & R studies
The purpose of this section is to outline the steps that can be taken to characterize the performance of gauges and instruments used in a production setting in terms of errors that affect the measurements.
2003. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S41 · Grade B
How to Test Your A3 Thinking
Reading an A3 in reverse helps A3 owners and their leaders confirm the use of a logical, fact-based thinking process.
2022-08-10. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S42 · Grade B
A case method for Sales and Operations Planning: a learning experience from Germany
It is performed at least once a month and is reviewed by management at an aggregate (product family) level.
2017. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S43 · Grade A
Local Authority Major Schemes: Benefits Management and Evaluation Framework
It also ensures those benefits are managed and monitored beyond the point of project completion.
2025. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S44 · Grade B
Proposal of a model for sales and operations planning (S&OP) maturity evaluation
The framework elaborated by Grimson & Pyke (2007), consists of five evolutionary stages, analyzed in the following categories: meetings and collaboration, organizational structure, measures of performance, information technology, and integrated planning.
2017-11-27. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S45 · Grade A
Performance Management Cycle
Performance elements and standards should be measurable, understandable, verifiable, equitable, and achievable.
2019-11-04. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S1201 · Grade A
e-Handbook of Statistical Methods: 6.3.1. What are Control Charts?
If a data point falls outside the control limits, we assume that the process is probably out of control and that an investigation is warranted to find and eliminate the cause or causes.
2003. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S1202 · Grade A
e-Handbook of Statistical Methods: 6.1.3. What is Process Control?
Out-of-control Action Plans (OCAPS) detail the action to be taken once an out-of-control situation is detected.
2003. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S1203 · Grade A
e-Handbook of Statistical Methods: 6.3.3.2. Proportions Control Charts
The proportion or fraction nonconforming (defective) in a population is defined as the ratio of the number of nonconforming items in the population to the total number of items in that population.
2003. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S1204 · Grade A
e-Handbook of Statistical Methods: 2.1.1. What are the issues for characterization?
A measurement process can be thought of as a well-run production process in which measurements are the output.
2003. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S1205 · Grade A
e-Handbook of Statistical Methods: 6.3.2. What are Variables Control Charts?
When following the standard Shewhart "out of control" rule (i.e., signal if and only if you see a point beyond the plus or minus 3 sigma control limits) you will have "false alarms" every 371 points on the average (see the description of Average Run Length or ARL on the next page). Adding the WECO rules increases the frequency of false alarms to about once in every 91.75 points, on the average (see Champ and Woodall, 1987 ).
2003. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S1206 · Grade A
e-Handbook of Statistical Methods: 5.1.2. What are the uses of DOE?
A product or process seldom has just one desirable output characteristic. There are usually several, and they are often interrelated so that improving one will cause a deterioration of another.
2003. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S1207 · Grade A
e-Handbook of Statistical Methods: 6.1.6. What is Process Capability?
Process capability compares the output of an in-control process to the specification limits by using capability indices.
2003. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
Open the recorded source ↗c12-S1208 · Grade A
e-Handbook of Statistical Methods: 5.7. A Glossary of DOE Terminology
Blocking: A schedule for conducting treatment combinations in an experimental study such that any effects on the experimental results due to a known change in raw materials, operators, machines, etc., become concentrated in the levels of the blocking variable.
2003. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.
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Keep the thread · chapter 12 of 14
Move the shuttle along the rack to preview any chapter: its sections, exhibits and reading time. Draft web edition. This research is not investment, legal or tax advice; illustrative models are not measured factory results.
The paper's rack · 14 boltsBolt length: reading time
01Part I: The measurement contract
A factory without an operating baseline cannot rely on hindsight, so GFT treats measurement as part of production from the outset.
02Part I: The measurement contract
Early targets should describe a controlled learning trajectory, with yield, rate and capability observed together rather than assumed away.
03Part I: The measurement contract
Strategic intent becomes an operating system when each line measure carries a decision, an owner, a feasible record and a guardrail.
04Part I: The measurement contract
Operational definitions, data-quality controls and measurement-system analysis must precede target comparisons and automated analytics.
05Part II: Measure the operating system
Good output is the result, while the production system must retain the component losses that explain why the result occurred.
06Part II: Measure the operating system
The quality system should connect first-pass yield, defect causes and variation so that inspection leads to prevention rather than sorting alone.
07Part II: Measure the operating system
Standard work, balanced capacity and order-level flow records must support the delivery promise before expediting becomes routine.
08Part II: Measure the operating system
A low nominal wage does not establish a low cost per good garment, so the people scorecard must include skill, supervision, attendance and working-time effects.
09Part II: Measure the operating system
Energy, water, waste and emissions become manageable only when each quantity has a declared boundary, source record and production denominator.
10Part III: Turn records into decisions
Source capture, master data and explicit stewardship turn daily logs into an operational asset without requiring a heavy platform on day one.
11Part III: Turn records into decisions
Daily correction, weekly problem solving and monthly reconciliation give each signal a forum, an authority level and a recorded response.
12Part III: Turn records into decisions
A corrective-action system should distinguish abnormal variation, test causes, verify effects and update standard work rather than count completed actions.
13Part IV: Scale with control
The factory should earn each digital step through reliable records, active management and verified improvement rather than buy a platform to compensate for their absence.
14Part IV: Scale with control
GFT recommends four gated stages: clean capture, active cadence, verified improvement and a data-driven floor, with value measured in the same system throughout.