Operations Management Group Technology (Gt)

Operations Management

Group technology (GT) layout is also referred to as cellular layout. This is a process by which factory processing is facilitated: dissimilar machines are grouped into cells, according to the components they work on. These components have the same weight, shape, and processing requirements. Most popularly used in metal fabricating, computer chip manufacture and assembly work, group technology layout has several advantages, but could also be problematic to implement and develop.

Advantages include that better human relations are cultivated within the often impersonal environment of the factory workshop. Small teams produce complete units of work. Each team member has a limited number of parts to work on, and builds expertise more quickly. Several production stages are combined, making the overall process less involved and less prone to mistakes. Successfully implementing a group technology layout has the overall effect of a faster production setup.

Changing from a process to GT layout may present several challenges. The first requirement is that parts be grouped into families with a common sequence of operations. This requires the implementation of a parts classification and coding system, which is computerized. Such processes can be expensive and time consuming upon implementation. The difficulty inherent in this is compounded by the necessity to identify dominant flow patters - also an initially complicated and time-consuming process.

Finally, the process is completed by physically moving the necessary machines and processes into cells. This could be problematic in terms of certain parts not being able to be grouped into specific families. In other cases, certain specialized machines cannot be located with specific parts, because they are generally used throughout the factory. Once all processes are in place, however, the advantages mentioned above are significant.

2) in a product planning problem, there are certain basic variables that can be controlled to a greater degree than others, while there are also four major costs involved. Factors associated with production planning can basically be grouped into internal and external factors. While the external factors are generally outside of the manager's control, the internal factors can be controlled to a greater degree. Internal factors can therefore be adjusted to some degree in order to create a feasible production plan.

The four internal variables that can be adjusted for an optimal production plan include workforce size, work hours, inventory, and order backlogs. The interaction of these four factors can be adjusted in order to optimize production and revenue. Strategies could for example include varying the workforce - hiring and laying off workers to match the output requirements. On the other hand, the workforce could remain stable while varying their work hours according to production requirements. A third possibility is maintaining both a stable workforce work hours. While employees benefit, shortages and surpluses created in this way are absorbed by factors such as fluctuating inventory, lost sales, and order backlogs. In such a case, there is a substantial risk of inventory becoming obsolete, while production costs are also increased.

The four costs involved include basic production, changes in production rate, inventory holding, and backlog costs. Specifically, the first includes material costs, labor costs, and compensation. The second involves hiring, training, and costs involved in laying off workers. Inventory holding costs involves storage, insurance, taxes and obsolescence, while backlogs costs are those incurred by expediting, loss of customer goodwill, and cancelled orders because of product unavailability. Backlog costs are difficult to quantify, because they involve a larger factor than only financial costs. The loss of customer goodwill for example has an effect on both current and future revenue.

3) a tracking signal is a useful device in forecasting market trends. It indicates the deviations above or below the actual market occurrence as compared to the forecast for these markets. This is useful in adjusting the current forecast model to be more accurate for future forecasts. If the tracking signal for example indicates a deviation of -2, the forecast model is too high above the mean of actual occurrence, and needs to be adjusted accordingly. Concomitantly, a positive deviation indicates a deviation below the mean of occurrence, which reflects that the forecasting model should be adjusted upward.

A perfect forecasting model would incur a sum of actual forecasting errors that amount to zero. This means that no forecasting model can be perfectly aligned to the actual occurrence at all times, but the deviation should be close to zero in order for the model to be effective. Furthermore, it is also important to take into account the price of the demand items. A high-priced items for example should be monitored more frequently than those items that are priced at a lower level.