Work Measurement and Time Study Course

Lesson 1 • Ethical and Legal Considerations

Addresses worker rights, informed consent, and regulatory obligations in time study. Analysts must balance organisational needs with fair and transparent measurement practices.

Lesson 2 • History and Purpose of Time Study

Traces time study from early industrial engineering to modern practice. Establishes why systematic measurement is essential for productivity and cost control.

Lesson 3 • Types of Work and Work Content

Classifies productive, non-productive, and incidental work categories. Understanding work content guides analysts in selecting appropriate measurement methods.

Lesson 4 • Measurement Systems and Units

Covers time units, decimal minutes, and time measurement units used in industry. Consistent unit usage prevents calculation errors in all subsequent analyses.

Lesson 1 • Principles of Element Identification

Explains rules for defining elements that are distinct, measurable, and consistent. Proper identification ensures timing data is comparable across observers and cycles.

Lesson 2 • Handling Special Work Situations

Addresses machine-controlled, concurrent, and contingency elements in complex jobs. Analysts learn to classify and record atypical work without distorting standard time.

Lesson 3 • Documenting the Element Breakdown

Teaches standardised formats for recording element descriptions and sequences. Clear documentation enables study replication and cross-analyst consistency.

Lesson 1 • Continuous Timing Procedure

Guides analysts through the continuous read method step by step. This method captures all elapsed time and minimizes data loss during complex studies.

Lesson 2 • Data Recording and Field Forms

Introduces standardised time study observation sheets and digital entry tools. Consistent recording practices enable accurate post-study calculation and audit trails.

Lesson 3 • Cycle Selection and Sample Size

Explains statistical principles for determining how many cycles to time. Adequate sample size ensures the resulting standard time is statistically reliable.

Lesson 4 • Stopwatch Types and Equipment Setup

Compares mechanical, digital, and software-based stopwatches for field use. Proper equipment selection and calibration prevent systematic timing errors.

Lesson 1 • Concept of Normal Performance

Defines normal pace using industry-standard benchmarks and reference films. A shared definition of normal is required before any rating system can be applied consistently.

Lesson 2 • Westinghouse Rating System

Covers the four-factor Westinghouse method: skill, effort, conditions, and consistency. Students apply factor tables to derive a composite performance rating.

Lesson 3 • Pace Rating and Objective Rating

Introduces single-factor pace rating and Mundel's objective rating method. Objective rating separates pace from difficulty to reduce inter-rater variability.

Lesson 4 • Rating Calibration and Practice

Uses video benchmarks and group exercises to calibrate analyst ratings. Regular calibration sessions reduce systematic bias and improve inter-rater reliability.

Lesson 1 • Allowance Categories and Rationale

Defines personal, fatigue, and delay allowances and the logic behind each. Understanding allowance purpose prevents arbitrary or inflated standard times.

Lesson 2 • Documenting and Validating Standard Times

Covers standard data sheets, revision triggers, and validation against historical output. Proper documentation ensures standard times remain accurate and traceable over time.

Lesson 3 • Fatigue Allowance Determination

Applies ILO and industry fatigue tables to quantify physical and mental work demands. Systematic fatigue assessment protects worker health and produces defensible allowances.

Lesson 4 • Delay Allowance Studies

Uses work sampling and time logs to measure unavoidable delay frequency and duration. Empirical delay data replaces guesswork with statistically grounded allowance values.

Lesson 1 • Validating and Comparing PMTS Results

Compares PMTS-derived standards against stopwatch study results for the same task. Discrepancy analysis builds analyst judgment about method selection and accuracy limits.

Lesson 2 • MTM-1 Motion Categories

Covers the nine MTM-1 motion categories: reach, move, turn, grasp, position, release, disengage, eye motions, and body motions. Correct category selection is critical for accurate synthesis.

Lesson 3 • MTM-1 Analysis Procedure

Walks through a complete MTM-1 analysis from motion description to TMU summation. Students practise on standardised exercises before applying the method to real tasks.

Lesson 4 • Higher-Level PMTS: MOST and MTM-2

Introduces MOST and MTM-2 as faster, aggregated alternatives to MTM-1. Students learn when higher-level systems provide sufficient accuracy with reduced analysis time.

Lesson 1 • Study Design and Sample Size Planning

Covers confidence level, accuracy level, and preliminary proportion estimates for sizing a study. Correct design prevents under-sampling and wasted observation effort.

Lesson 2 • Work Sampling Theory and Applications

Explains the statistical basis of work sampling and its industrial applications. Sampling is cost-effective for long-cycle, irregular, or multi-machine work unsuitable for stopwatch study.

Lesson 3 • Analysis and Standard Time from Sampling

Converts work sampling proportions into standard time using performance rating and output data. Students interpret results and present findings with confidence interval statements.

Lesson 4 • Random Observation Scheduling

Teaches methods for generating and scheduling truly random observation times. Randomness prevents observer anticipation and ensures unbiased activity snapshots.

Lesson 1 • Maintaining and Updating Standard Data

Establishes revision triggers, audit schedules, and version control for standard data libraries. Outdated data silently corrupts labour standards and must be managed proactively.

Lesson 2 • Building Tabular Standard Data

Covers collecting elemental times across job variations and organising them into lookup tables. Tabular data is the simplest standard data form and suits low-variety operations.

Lesson 3 • Standard Data Concepts and Benefits

Defines standard data as pre-analysed time values organised for reuse across similar jobs. Standard data reduces study cost and improves consistency across the standards database.

Lesson 4 • Regression-Based Standard Data

Applies linear and curvilinear regression to model time as a function of job parameters. Regression models handle continuous variables more precisely than lookup tables.