Friday, October 28, 2011


Document related
·         Uncontrolled documents in the manufacturing floor- including illegibility, scribbling and mutilations
·         Procedure does not reflect the practice and vice versa.
  • Vendor base not being consistently updated with current revisions of drawings and documentation.
  • Current and Obsolete drawings being used simultaneously
  • Approved vendor list not updated regularly.
  • Critical process instructions not available at the place of use.
  • Instructions displayed in workplace found not under document control.
  • Unauthorised and undated hand-written changes made to procedure
  • Inconsistency in the revision status of same document at different places of use
 Product related
  • No clear identification of good and non conforming material.
  • Incorrect storage of materials.
  • Shelf life products not assessed periodically
  •  Over aged product in storage
·         Management related
  • Internal quality audits not carried out at specified intervals.
  • Actions minuted in the management review committee meetings  not followed up for
  • completion.
  • Product non-conformances at in-process stage not selected for corrective actions.
  • Internal quality auditors carrying out audits without formal training
·        Records related

  • Quality record  not legible
  • Improper indexing /storing of records
Solutions to the above lie in the following
  • Design simple and operable management systems- adopt KISS- Keep It Simple and Short
  • Bring in all the documents under management system purview- never have any procedure/template outside the system
  • Assign process owners and make them accountable for the process performance
  • Make the system user-friendly and comprehensive
  • Create, store and retrieve documents and record using soft copies and avoid hard copies as much s possible
  • Bring in a culture of adhering to systems by periodical training to users
  •  Provide leadership in system maintenance


Wednesday, October 26, 2011

IA Catchwords– Series 9


Observe is an important catchword in Auditing. In fact, an experienced Auditor uses this effectively, in identifying non-compliances and incompatibilities during Auditing. Non-compliance occurs, when there is an observed gap between documents and practices and incompatibility occurs, when the auditee provides a process explanation which is different from the observed ones. In both the cases “observations” by the auditee is critical.
Given below are 10 commandments for the Auditors
  1. Observe the process operations in action- conversion of inputs to outputs
  2. Observe the deployed process controls for correctness and effectiveness
  3. Observe the records of process monitoring for correctness and completeness- including control charts and process cards
  4. Observe the workplace arrangement
  5. Observe the workplace safety
  6. Observe the process document dynamics- how often the process operations have been revised/improved
  7. Observe the body language of the auditee to verify the process knowledge
  8. Observe the comfort and confidence in the auditee’s answers
  9. Observe the handling and retrieval of records maintained
  10. Observe the storage & handling of process rejects
Hope you would be able to practice the above. Please share your experiences. Good Luck

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

Sunday, October 23, 2011

Training Videos for Safety in workplace- OHSAS 18001

IA Catchwords– Series 8

Not explained

Process realization activity is to be documented as per the requirements, needs of the process and the competency of the personnel. Process explanations are to be documented to ensure that the process is carried out to meet the requirements. If it is observed that the absence of such explanations had caused or potential to cause non-conformities, then it is necessary to provide explanations either in the form of documentation or visual displays.

Not trained

Training of personnel is critical to any activity. Training is to be planned both for meeting the existing process/product requirements and enhancing the competency of operating personnel. If it can be concluded that lack of training had resulted in process/product/service non-conformities, then it is important that training is identified as a means of closure of the non-conformity. in fact, "not trained" is one of the common causes of analysis, if proper RCA (Root Cause Analysis) is carried out. This is true in not only in product realization or maintenance or marketing. For example, if a company has identified that a lower hit-rate is an effect and the cause is due to inadequate training of marketing/application personnel in understanding clients requirements, then the same is to be addressed.  

Thursday, October 20, 2011

QMS Data Management- Series 1

Data management includes the following
·         Identification of opportunities for data identification
·         Prioritization/classification of data in each of those opportunities
·         Identification of data to be managed
·         Planning for data management
·         Systematic arrangement for data collection
·         Data collation
·         Analysis
·         Identification and implementation of corrective and preventive actions

QMS clause No. 8, identifies Measurement, Analysis and Improvement and focuses on measurement of QMS and calls for determination of applicable methods, including statistical techniques. Data planning however starts from Cl. No. 4.1, when there is a need to monitor, measure, and analyze QMS processes. In addition, clause number 8.2.1, 8.2.2, 8.2.3, and 8.2.4 also need to be managed.

Records form a major chunk of data management. Records requirement are specified and needs to be addressed. Records provide evidence that the realization processes meet the QMS requirements. Hence, management of data from those records forms the basis of the improvements. Records could be in the form of sheer information and measurable data. Such measureable data management is what is needed in the Clause No. 8.

Data measurement

Records form the basis for data identification.
Below given are some of the areas of data measurement:
·         Process related- 5.6, 6.2.2, 6.3, 7.2, 7.3, 7.4.1, 7.4.2,7.4.3, 7.5.1,7.5.2, 7.5.3, 7.5.4,7.5.5, 7.6, 8.2.1, 8.2,2,8.2.3
·         Product/service related- 7.2, 7.3,7.4.3,7.5.1, 7.5.3, 8.2.4,

The first step is to segregate information and monitorable and measurable data from the records.
Data management includes systematic collection of data from the processes and product/service realization
Data collection is done in such a manner, that they can be collated and analysed
Designing of various formats/templates/checklists/control charts to be used for data collection play an important role. Frequency of collection and method of recording data is planned to provide adequate information on the effectiveness of the control of the process/product/service.
A poorly designed format/template can defeat the purpose of data measurement, without providing required information. Once the data is collected, a collation matrix would help in consolidating them and help in prioritizing for subsequent analysis.
A collation Matrix would typically contain data on various parameters of each process being monitored, frequency of data collection, and the source of data collected.
Data analysis would be discussed in the next article. Meanwhile, initiate data collection and collation. Any help, do not hesitate to contact. Good luck