In this challenging world, people understood the words of Quality, Quality Management and even Total Quality Management (TQM). However not many understood what does it meant in the perspective of Business Management or even work improvements. It is actually important even to non-profitable organizations such NGOs and not neglecting to GLC or Government Link Organizations.
Discussing on quality, the application of it could be implemented in multi-international corporations, multi-national corporations, medium companies, small companies, Government Link Companies, Non-profitable companies, associations, society, and even family level and individual level.
Talks and forums have been held every where on TQM and some even went for a short course sent by their organizations. Some learn in some degrees or post graduate but how many has learnt in the right flow with concept and able to apply it in their daily life. It is found that some has really learned it, but has not reach the level of integrated it with statistical studies and statistical application. Only if we have learned TQM, that is the concept, theories, process, process tools such as PDSA (Plan Do Survey Act) or the DMAIC (Define Measure Analyze Improve Control), and then we must integrate with the statistical measurement. After developing all these measurement, the last part is to transfer it to the acceptable or manageable control tools. There a numbers of it but most scholars say it is 7 best control tools i.e. Pareto Chart, Histogram, Process Flow Diagram (Fish Bone), Run Chart etc. It is found that one of the most popular is Pareto Chart, Run Chart and Process Flow Chart. However in certain industries some would use different control tools accordingly.
One of the most important to analyze the efficiency of the business process using statistical analysis is a comparative analysis between Traditional Yield (Y) and Yield Metrics that is First Time Yield (FTY) for a main process and Rolled Through put Yield (RTY) for small sub processes.
It is found that that the value of FTY is lesser than Traditional Yield and it resembles a more accurate Yield Value calculation. If the rate of FTY is questionable, then the whole process flow must be measured. The RTY then should be used to measure at each process where RTY = FTY1 x FTY2 x FTY3 … depending on the number of the process.
Only integrating TQM with statistical evaluation would be beneficial to all users of TQM or to all TQM implementers.
As a case study, in 2002 one medium size motorcycle assembly plant in Queensland, has promoted that they are one of the most efficient assembly plant in Australia, at the rate of 98.6% out put or yield value. The yield value was calculated based on the production to assemble 352 motorcycles per months and completed for sales is 347 units. However, 103 units are to be rework after QAQC and leaving only 5 units as scraps.
In 2006, after the Production Manager retired, they have engaged one new production manager graduated form USC to be the Production Manager. She found out that after using Yield Metrics, the production rate or efficiency is only 70.75%. She then later found out after subdividing all the production process into sub-production processes into 5 groups, the Yield metrics turn to be only 51.8%.
After presenting to the Managing Director (MD), the MD questioned her findings and she managed to explain the findings and the integration of statistical analysis into her findings. She has also proposed to the MD the new way of using monitoring tools for the production control as one of the most effective way in implementing control system. The proposed control tools are run chart and Pareto Chart. The Managing Director was happy and requests her to implement TQM for improvements. Later after a year she is then promoted to Plant Manager, taking responsibility in procurements, production/assembly, Sand Blasting and Painting, QAQC, Inventory, and Distribution to outlets.
Discussing on quality, the application of it could be implemented in multi-international corporations, multi-national corporations, medium companies, small companies, Government Link Companies, Non-profitable companies, associations, society, and even family level and individual level.
Talks and forums have been held every where on TQM and some even went for a short course sent by their organizations. Some learn in some degrees or post graduate but how many has learnt in the right flow with concept and able to apply it in their daily life. It is found that some has really learned it, but has not reach the level of integrated it with statistical studies and statistical application. Only if we have learned TQM, that is the concept, theories, process, process tools such as PDSA (Plan Do Survey Act) or the DMAIC (Define Measure Analyze Improve Control), and then we must integrate with the statistical measurement. After developing all these measurement, the last part is to transfer it to the acceptable or manageable control tools. There a numbers of it but most scholars say it is 7 best control tools i.e. Pareto Chart, Histogram, Process Flow Diagram (Fish Bone), Run Chart etc. It is found that one of the most popular is Pareto Chart, Run Chart and Process Flow Chart. However in certain industries some would use different control tools accordingly.
One of the most important to analyze the efficiency of the business process using statistical analysis is a comparative analysis between Traditional Yield (Y) and Yield Metrics that is First Time Yield (FTY) for a main process and Rolled Through put Yield (RTY) for small sub processes.
It is found that that the value of FTY is lesser than Traditional Yield and it resembles a more accurate Yield Value calculation. If the rate of FTY is questionable, then the whole process flow must be measured. The RTY then should be used to measure at each process where RTY = FTY1 x FTY2 x FTY3 … depending on the number of the process.
Only integrating TQM with statistical evaluation would be beneficial to all users of TQM or to all TQM implementers.
As a case study, in 2002 one medium size motorcycle assembly plant in Queensland, has promoted that they are one of the most efficient assembly plant in Australia, at the rate of 98.6% out put or yield value. The yield value was calculated based on the production to assemble 352 motorcycles per months and completed for sales is 347 units. However, 103 units are to be rework after QAQC and leaving only 5 units as scraps.
In 2006, after the Production Manager retired, they have engaged one new production manager graduated form USC to be the Production Manager. She found out that after using Yield Metrics, the production rate or efficiency is only 70.75%. She then later found out after subdividing all the production process into sub-production processes into 5 groups, the Yield metrics turn to be only 51.8%.
After presenting to the Managing Director (MD), the MD questioned her findings and she managed to explain the findings and the integration of statistical analysis into her findings. She has also proposed to the MD the new way of using monitoring tools for the production control as one of the most effective way in implementing control system. The proposed control tools are run chart and Pareto Chart. The Managing Director was happy and requests her to implement TQM for improvements. Later after a year she is then promoted to Plant Manager, taking responsibility in procurements, production/assembly, Sand Blasting and Painting, QAQC, Inventory, and Distribution to outlets.
It has proven that TQM is a very effective way in improving an organization out put and for that reason in modern strategic implementation control and monitoring, TQM has been one of the crucial components besides six-sigma. Some scholars wrote that integration of six-sigma into TQM has proven a higher output standard of improvements
