Conducting the Knowledge Transfer
February 12, 2025
How the Ubiquitous Smartphone has Revolutionized B2B and B2C Commerce Who doesn’t own a Smartphone? Right from teenagers to senior citizens and from businesspersons to business leaders, Smartphone ownership is Ubiquitous and all pervasive. Indeed, it is estimated that nearly 80% of the world’s population is now connected to each other through the mobile phones […]
More Losers than Winners The previous articles in this module covered the topic of globalization in depth. Some of the points of discussion were about how globalization has succeeded in lifting millions of people out of poverty. While accepting this fact, it is also the case that globalization has created income inequality which when coupled […]
Why do we determine whether a computerized decision support system application is worth considering or not? Why is there a need to predict the actual impact of a proposed DSS? In short, the question is – why is it necessary to evaluate a decision support system project? The answer is simple. It’s done to assess […]
The biggest ever trade war is underway. China and the United States, which are the two largest economies in the world, are at loggerheads. President Trump drew first blood when he imposed duties on steel and aluminum imported from China and many other countries. However, the Chinese government was not far behind either. China unveiled […]
Much is being said and written about the emerging digital economy with all its promise of techno-utopia and the perils of technology taking control of our lives. Indeed, while some experts have cautioned against surmising that technology would solve all the problems of humankind and lead us into a future of abundance, the mainstream view […]
Cyclical Pattern: A cyclical pattern is defined as a predictive situation in which data points increase and decrease the process mean in a manner which is repetitive. While this may sound like a mouthful, we are all intuitively aware of what a cycle means. In the case of control charts, cyclical patterns signify special cause variation because they are not random. Cyclical patterns may emerge out of the reasons that have been discussed below:
Operator Fatigue: The most common cause of cyclical variation is operator fatigue. This usually hints at a much larger problem of incorrect job design. Many times, job designs require excessively strenuous effort taking by the operator. This may manifest itself in the form of cyclical movements as the operator is simply unable to work at the same level of productivity throughout the day.
Production Equipment: Another common cause of cyclical pattern is the wear and tear of the production equipment. Many times the voltage and power also fluctuates causing the efficiency to fluctuate in predictable non-random patterns.
This pattern therefore bring to the managements notice, patterns that if left undetected, could have resulted in a process going out of control.
Trend Pattern: A trend pattern is defined as a situation wherein the data points lie between the specification lines drawn on the control chart but display a specific trend. A trend is the movement of seven consecutive points in one direction. The direction could be increasing or decreasing. Statistical studies have shown that less than seven points can lie in one direction in a random process. However, if 7 or more data points lie in one direction the cause needs to be investigated as it could be a special cause variation.
Common examples of a trend variation include the learning curve and noise factors. The examples related to each of the above are as follows:
Learning Curve: The people that perform the work learn by doing it. Over a period of time, they become experts in the work that they perform and take less and less time to do it. This reflects in the control charts in the form of a trend. Over a period of time, the data values pertaining to cycle times will be falling whereas those related to productivity will be increasing. The management needs to take a note of this and try to train employees in such a way that they are already fairly well versed with the task by the time they come in to work.
Noise Factors: Noise factors are the disturbances that the process may come across over a period of time. A good example would be to consider the fact that the average time taken by a process is likely to go up as the volume increases. This is because as the volume increases workers feel overwhelmed with the amount of tasks they are handling and communication between them becomes difficult leading to the trend appearing.
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