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Example (ii) A company manufactures parts for a car. The company receives each day the first thing in the morning the orders that should deliver in the following day. The section of the companys plant takes charge of two types of parts, A and B. All the works require the work of a technician on a machine. The production rate (PR) varies according to the type of the part, 3 pieces/hour for those of type A and 5 pieces/hour for those of type B. The plant works with four different clients who may or not place an order in a given day. From the past historical data, the following distribution of probability is used to determine the number of orders received a day (NOD). NPD Probability 0.10 0.10 0.30 0.40 0.10
Since all the clients have a very similar production, the probability for a type of parts that they place an order is the same. That is, for part A, it is equal to P(type pieces order A)0.3. For part B, P(type pieces order B) 0.7 The size of the orders (SO) also variable and follows a uniform distribution, between 50 and 100 pieces. The normal working hours per a workday is 8 hours. Each worker charges $18,000 per year but each overtime costs $10/hour. Each machine costs $1,200 per year Develop a flow chart for a simulation model which objective is to determine the number of workers (NW) and machines (NM) that minimize the total price. (Assume: A year comprises of 365 working days.)
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