Understanding Quality Costs and Management Techniques

Actual Capacity

Actual Capacity

Rate of output actually achieved.

Efficiency

Actual Output / Effective Capacity x 100

Diseconomies of Scale

The output rate is more than the optimal level. Increasing the output rate results in increasing average unit costs.

Type II Error

Concluding a process is in control when it is not. (e.g., allowing defective products to reach customers)

Design Capacity

The maximum output rate or service capacity an operation, process or facility is designed for (i.e., theoretical perfection).

Effective Capacity

Design capacity minus allowances such as personal time, and maintenance. The capacity a firm expects to achieve given current operating constraints.

Economies of Scale

The output rate is less than the optimal level. Increasing the output rate results in decreasing average unit costs.

Optimal output rate

Cost per unit is the lowest for the production unit.

Project life cycle

1. Definition: at which point the organization recognizes the need for a project or responds to a request for a proposal. 2. Planning: Spelling out the details of the work and providing estimates of the necessary human resources, time, and cost. 3. Execution: During which the project itself is done. This phase often accounts for the majority of time and resources consumed by a project. 4. Termination: During which closure is achieved - reassigning personnel, dealing with leftover materials, equipment, etc.

Appraisal costs

Costs incurred when the firm assess the performance level of its processes.

Prevention costs

Costs related to reducing the potential for quality problems and preventing defects before they happen. (e.g., training, research, quality improvement programs, design costs.)

Failure costs

Costs caused by defective parts or products or by faulty services.

Internal failure costs

Failures discovered before delivered to customers. (e.g., loss of production time, investigation costs, etc.)

External failure costs

Failures discovered after delivery to the customer. (e.g., warranty costs, handling of complaints, liability, replacements, etc.)

TQM

A philosophy that involves everyone in an organization in a continual effort to improve quality and achieve customer satisfaction. A holistic approach to long-term success that views continuous improvement in all aspects of an organization as a process.

Six Sigma

A measure of quality that strives for near perfection. Statistically it means having no more than 3.4 defects per million opportunities in any process.

Flowchart

A diagram of the steps in a process. A visual representation of a process.

Check Sheets (or Checklists)

A tool for organizing and collecting data; a tally of problems or other events by category. A form used to record the frequency of occurrence of certain process failures.

Histogram

A chart of an empirical frequency distribution. A summarization of data measured on a continuous scale, showing the frequency of distribution of some process failure.

Pareto Analysis

A diagram that arranges categories from highest to lowest frequency of occurrence. Technique for classifying problem areas according to degree of importance and focusing on the most important.

Scatter Diagram

A graph that shows the degree and direction of relationship between two variables. Useful in deciding if there is a correlation between the values of two variables.

Control Chart

A statistical chart of time-ordered values of a sample statistic. Useful in detecting the presence of correctable causes of variation.

Run Chart

Tool for tracking results over a period of time. Useful in identifying trends or other patterns that may be occurring.

Cause-and-Effect Diagram (Fishbone Diagram)

A diagram used to search for the cause(s) of a problem. Identifies categories of factors that might be causing problems.

Random Variation (Common Variation)

Natural variation in the output of a process, created by countless minor factors. (e.g., older machines exhibiting natural variability.)

Assignable Variation (Special Variation)

A variation whose cause can be identified (assigned to specific causes). A non-random variation. (e.g., defective materials, human factors, equipment that needs adjustment, etc.)

Type I Error

Concluding a process is not in control when it actually is. (e.g., discarding good products)

Utilization

Actual Output / Design Capacity x 100