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Inventory Control
The strategic importance of efficient Supply Chain Management is today fully recognized by top management. The total investment in inventories is enormous, and the control of capital tied up in raw material, work-in-progress, and finished goods offers an important potential for improvement. At the same time, advances in information technology have drastically changed the possibilities to apply improved inventory control techniques. Furthermore, the recent progress in research has resulted in new and more general methods that can reduce the supply chain costs substantially.
Industrial competitiveness : Cost reduction
The objectives of industrial management are: - Implementation of the policy adopted by the owners or the board of directors - Optimum return on investment - Efficient utilization of Men, Machine and Money. In other words, industry must make profit. Manufacturing represents only one aspect of the activities of industrial management. Present-day manufacturing methodology does not consider making profit as their primary objective. The manufacturing process requires the knowledge of many disciplines, such as design, process planning, costing, marketing, sales, customer relations, costing, purchasing, bookkeeping, inventory control, material handling, shipping, and so on.
Fuzzy probabilities : New approach and applications
In probability and statistics we often have to estimate probabilities and parameters in probability distributions using a random sample. Instead of using a point estimate calculated from the data we propose using fuzzy numbers which are constructed from a set of confidence intervals. In probability calculations we apply constrained fuzzy arithmetic because probabilities must add to one. Fuzzy random variables have fuzzy distributions. A fuzzy normal random variable has the normal distribution with fuzzy number mean and variance. Applications are to queuing theory, Markov chains, inventory control, decision theory and reliability theory.
Forecasting with Exponential Smoothing : The State Space Approach
Exponential smoothing methods have been around since the 1950s, and are the most popular forecasting methods used in business and industry. Recently, exponential smoothing has been revolutionized with the introduction of a complete modeling framework incorporating innovations state space models, likelihood calculation, prediction intervals and procedures for model selection. In this book, all of the important results for this framework are brought together in a coherent manner with consistent notation. In addition, many new results and extensions are introduced and several application areas are examined in detail.
