Wednesday, October 26, 2011

QMS Data Management- Series 2

Collation of data is done using a data matrix. The next step is prioritizing the parameters towards process improvements. Prioritization is based on the criticality of parameters/processes, expectations of customers, stakeholders, etc., The next step would be to carry out data analysis.
Data analysis consists of using various statistical tools. Statistical methods help to understand processes, to bring them under control, and then to improve them.  If one is running a high-volume product process, Control Charts help in Pareto Chart and Cause-and-Effect chart are the most useful tools for others. When we are dealing with simple individual processes, the above can be applied effectively. However, in an organization where many processes are involved, it is better to deal with them at a global level, since there are multiple process owners.
A sensible and effective approach to carry out Data Analysis would be by using a Data Analysis Team (DAT) drawn for the specific purpose. The following steps are recommended.
·         As the Team Leader, Management Representative (MR) takes the initiative in forming this DAT. He selects the team members having good analytical skills and process knowledge in his/her area of work.
·         MR has to ensure that at least one member is represented by each process/function identified for improvement.
·         Brainstorming sessions would make the job easier for the MR.
·         The first step is to study the existing system, and identify potential causes of root causes and prepare a Ready Reckoner
·         The various heads under which these Root Causes are identified could be
o   Men
o   Machine
o   Measurement
o   Method/System
o   Materials
o   Documentation
·         One must realize that the various potential root causes fall under 80/20 rule- meaning that common causes are 80% and only 20% are special to an organization.
·         Some examples of potential root causes under each head are
o   Men- lack/less of communication skills, lack/less of commitment/attitude of personnel, lack of product knowledge, lack of product knowledge
o   Machine- improper machine/tools/dies/jigs setting, inadequate/improper machine maintenance, inadequate machine/equipment performance
o   Measurement- inadequate test equipment, improper recording, inadequate calibration
o   Method/system- inadequate monitoring/controlling of processes, inadequacy in operational planning, inadequate supplier control
o   Materials- improper choice of parts/components, material mix-up, alternative materials used
o   Documentation- inadequate process documentation, inadequate recording, non-availability of controlled documentation
·         Deployment of the ready-reckoner in completing the data analysis would be discussed in the next article. Meanwhile, initiate and go ahead with forming DAT. Any help, do not hesitate to contact. Good luck


Post a Comment

Subscribe to Post Comments [Atom]

<< Home