4-M version

The three most probable causes may be circle for the development of an action plan. Generally, the 4-M (manpower, material, method, and machine) version of the fishbone diagram will suffice. In a laboratory environment, measurement is a key issue.

The categorization under People include:

1. Inadequate Staffing

2. Inadequate Skills

3. Lack of Experience

4. Lack of Process knowledge

The categorization of Measurement include collection consistency and CTP’s not measured.

The categorization under Mother Nature include:

1. Day of the week

2. Week of the month

3. Month of the year

4. Holiday season

The categorization under materials include:

1. Lack of Documentation

2. Lack of Knowledge Base

3. Lack of EscalationMatrix

And the categorization under Machine include:

1. Server Downtime

2. Workstation Downtime

Measurements of process inputs and outputs can be used to optimize the process being measured. Process inputs may be raw materials, human resources, or services. All inputs have some quantifiable measurement,including human effort and skill level. Process input requirements should be stated so that key measures of input quality can be controlled. Measurements within the process can also be used as effective controls.

Once process capabilities are known, output measures can be used to monitor if the process has remained in control. Process database of the organization has details of input measures, process controls, process measures and outputmeasures. Feedback from downstream process measurementscan be used to improve an upstream process. For example, electrical testing for solder shorts can be used to optimize a circuit board soldering operationeven if it is several processes upstream from the testing operation. When considering the entire organizational feedback system, complex interrelationships are likely to exist. This is where planned experimentation anddesigning for six sigma comes into play. Planned experimentation deals with isolating the effects of several different, independent variables on a process.