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DSC335FINAL - Quality and Performance quality hard to...

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Quality and Performance : quality hard to define. Two phases: design and implementation. Type 1 : Design quality-inherent value of a product or service to customers by its design, ex: performance, features, reliability). Type 2 : conformance quality- degree to which a product or service design quality are implementation by production or service delivery process (building design to sustain, if construction doesn’t endow the building then the conformance quality is low). TQM -philosophy for managing the entire organization so that it excels on all dimensions of products and services (3 principles: customer satisfaction, employee involvement, continuous improvement). SIX SIGMA : perfection, eliminate defects, made by Motorola, extended by GE. Falling out of “Range” allowed by design is considered a defect, to six sigma intervals, contains 99.99999% of all possible samples. Seeks to reduce variability in the processes that lead to product defects Supply Chain : Bullwhip effect is a phenomenon observed in supply chains where the order variability increases as one moves upstream from retailers to wholesalers to distributors and to factories, the variance in order quantities at the upstream members is greater than that at downstream. Causes problems : excess raw material cost, excess capacity, excess inventory, increased transportation. How it happens : demand forecasting, order bathing, price variations, rationing game. 1. DFs are updated based on observed demand, if you observe a demand rise you will adjust DF upward and place a larger order to prepare for future demand. EX: retailer receives random demand w. 100 units/wk. wholesaler’s supply lead time is 4 wks. Beg of week, retailer places order before demand realizes, meets demand from inventory. The retailer employs a naïve demand forecast approach, demand in future weeks=realized demand in current week. If demand is always 100.w, the retailer orders 100 per week. In current week, demand drops by 10% to 90. End of the current week, ending inventory=10. For next 4 weeks demand forcast=90/wk, received quantity=100/wk. The retailer perceive that inventory increase by 10 units/wk, the beg. Inventory in the 5 th wk is 10+40*10=50. If retailer orders Q unit now, it wil arrive in the 5 th week. In the 5 th week, the retailer expects the total on-hand inventory before meeting demand =50+Q, demand forecast for the 5 th week=90, to meet demand the retailer orders Q=90-50=40. The order to the wholesaler drops from 100 to 40, by 60%. Lag in Info flow, overreaction to shortage or overage. Fix it: shorten resupply lead time, better forecast, sharing demand info across supply chain, current practice. 2. Order batching: Larger ordering (fixed) cost, EOQ model where demand is flat, variability in customer demand is zero. If fixed cost is very small, retailer orders frequently in small batches, if retailers ordering fixed cost is very high, retailer orders less frequently, but in larger batches . 3. Price Variation: supplier promotion.
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