TOTAL QUALITY MANAGEMENT

What is TQM?
TQM stands for Total quality Management System.
Is the present system of collecting data is adequate?
Data and facts are fundamental to all improvement efforts. Data helps us make better decisions, gain new insights and measure our progress. All best-of-industry quality processes depend upon data collection.
Most measurement data were collected manually. For manufacturing processes, the data often come from measurement instruments used to collect spatial, environmental, electrical, mechanical or physical characteristics from the part being manufactured.
Present systems the collections of data by the following methods are not sufficient.
Surveys
Focus groups
Data sheets
Check sheets
Interviews and
Direct observation.

How warranty and quantity losses obtained?
By using various data collection tools this may be redefined.
v Basic Concepts: planning, stratification, bias, validity, reliability, sampling
v Exercise: concepts of stratification, sampling
v Data Collection Steps
v Review of various data collection methods: direct observation, data sheets, check sheets, surveys, interviews, focus groups, work flow diagrams, concentration diagrams
v Exercise: customer satisfaction surveys
v Exercise: flow diagram
v Data Presentation: the basic charts such as bar charts, line charts, run charts, scatter diagrams, pie charts; high tech charts such as radar charts, control charts
v As computers became smaller, more affordable and faster, this function was turned over to them, decreasing the time and increasing the accuracy of data collection.
v Setting up an automated shop floor data collection system involved straightforward decision making:
v Bring a dedicated data collection system, had one custom-designed for you, or you put one together yourself using a PC, a data collection box, a multiplex or and some sort of data collection software to communicate.
The software can be used to facilitate the following:
· The purposes of evaluation research (Exploring, Describing or Explaining)
· Deduction and Induction
· Cause and effect
· Hypothesis testing and grounded theory
· Types of evaluation designs such as Planning, Process, Outcome, Efficiency
· Action research
· Theories, goals and objectives
· Operationalization of concepts
· Sampling
· Units of analysis
· Measuring change
· Combining qualitative and quantitative data
· Ethical issues such as informed consent, anonymity and confidentiality
· Dissemination of results.