The Pros And Cons Of Fuzzy Logic

The current demand forecasting method is based on qualitative techniques more than quantitative ones. If the forecast is not accurate, the company would carry both inventory and stock out costs. It might lose customers due to shortage of supply or carry additional holding costs due to excess production. If the actual demand doesn’t match the forecast ones, and the forecast was too high, this will result in high inventories, obsolescence, asset disposals, and increased carrying costs. When a forecast is too low, the customer resorts to a competitive product or retailer. A supplier could lose both sales and shelf space at that retail location forever if their predictions continue to be inaccurate. The tolerance level of the average consumer

* Forecasting is an impartial strategic ingredient that will ensure apt base for reputable planning. Our forecast is always the first step in developing plans in running the business along with our future plans of growth strategies. With this tool, we are able to anticipate our sales within reason that then can allow for us to control our costs in conjunction with inventory which will then help us to enhance our customer service. Sales forecasting is a vital strategic tactic in our company’s methodology.

Forecasting is used in all businesses. Forecasting is used to help businesses decide how much they should produce and where to sell a product. Forecasting can aid a company in knowing the lifecycle of a product, which can help them to determine when and if they should discontinue a product. Forecasting can also help managers close the gap between supply and demand. If a forecast is properly predicted the supply of a product can satisfy the demand of the product. Forecasting is not always accurate however, and can lead to either over production of a product or underproduction of a product.

We first predict the annual demand for the year 1972 based on trend for 4 months of 1972 based on corresponding months of 1971.

Forecasting is the methodology utilized in the translation of past experiences in an estimation of the future. The German market presents challenges for forecasting techniques especially for its retail segment. Commercially oriented organizations are used to help during forecasting as general works done by academic scientists are not easy to come across (Bonner, 2009).

* As stated in the guidelines, we also assume that the mean of the demand is equal to the product of the mean of the forecasting error and the forecast itself, and the same for the standard deviation of demand;

Wang Ai-zhen , Ren Guo-feng [8] They determine the wash time by observing the input variables like Turbidity and turbidity change rate. In this paper the values are obtained from , the sensor of the washing machine i.e. Turbidity and turbidity change rate which is then passed to the information processing system , to process, the information was sent them to the controller. The value of input parameters are translated into fuzzy variables by the process of fuzzification, using MCU, accordance with the fuzzy inference rules and, the result is the fuzzy value. After defuzzification the crisp value, the washing time is obtained which we modify by the concept of soft computing neural

Seasonal factors: For example the demand for domestic energy over winter is greater than over the summer.

We first predict the annual demand for the year 1972 based on trend for 4 months of 1972 based on corresponding months of 1971.

But even this is not possible in case of a new product or innovation. A forecast of sales, demand, cash, requirements and several such business valuables are extremely essential for a business in order to be able to appropriately plan and conduct its operations in an effective and efficient manner. Yet, forecasts cannot be made accurately as there are several factors and changes in the current environment that leads to variations in forecasts and impacts or causes a manager to make changes in the forecasts.

Before, the concept of demand forecast was to serve the key functional groups in achieving their own interest. Facing the new challenges, forecast needed to be more accurate. And therefore it needed a new concept that is to have a consensus forecasting that would accurately reveal market demand and align the needs of key actors in the forecasting process. Leitax implemented two specific changes in forecasting process. The first one is to switch the focus from sell-in to sell-through and second one is to ignore capacity constraints.

Based on the case, there were two fundamental changes to standardize and improve the accuracy of forecasts. The first area was to "switch the focus of the focus of the forecasting process from sell-in to sell-through". This meant tracking closely what was sold in one region and shipped from another made forecasting market demand a more accurate exercise. The second area centered on ignoring capacity constraints to estimate demand. In the past, "forecasting was affected by perceptions of present and future supply chain capacity".

Business forecasting is the process of studying historical performance for the purpose of using the information gained to project future business conditions so that decisions can be made today that will assist in the achievement of certain goals. Forecasting involves taking historical date and using it to project future data with a mathematical model. Forecasts are extensively used to support business decisions and direct the work of operations managers. In this paper I will introduce different types of forecasting techniques.

Use for Forecasting – The impact of external forces makes it difficult to use the PLC as a forecasting tool. For instance, market factors not directly associated with the marketing activities of market competitors, such as economic conditions, may have a greater impact on reducing demand than customers’ interest in the product. Consequently, what may be forecasted

The availability of quality and reliable power is critical for economic development of the State.Growth in power consumption is an indicator of industrial,agricultural