Design changes resulted from a better integration of manufacture and installation. Quality improvement led to the re-engineering of brackets in order to make fixing easier and to cope with lesser tolerance onsite. The factory management stopped work on an ad-hoc basis when feedback was given, in order to give the whole workforce ‘one-point lessons’. This group learning process ensured equal delivery to all on a check, prevent and repair basis and saved the need for quality inspectors. Another problem was the deflection of the structural steel when fixing the units in the middle of spans, creating movement after two corridor units were complete and stressing the sealing between them. Both the design of the sealing and the rigidity of the structure were reviewed. Adjustments to the painting methodology were also made to ensure consistency of finish. The manufacturer is now in the process of extending its operations to other sites needing the same units and is developing its transport fleet to cope with a longer turnaround time.
A random variable x has the following empirical distribution. x 1 2 4 6 8 10 f(x) 0.10 0.20 0.25 0.20 0.15 0.10 Plot the cumulative distribution and find the values of x corresponding to the following two digit random numbers: 05, 45, 62, 93 (8 Marks) b. The distribution of inter arrival times in a single server model is: T : 1 2 3 f(t) : ¼ ½ ¼ and the distribution service time is: S : 1 2 3 f(s) : ½ ¼ ¼ Develop a simulation table using the two digit random numbers 12, 40, 48, 93, 61, 17, 55, 21, 85, 88 to generate arrivals and 54, 90, 18, 38, 16, 87, 91, 41, 54, 11 to generate the corresponding service time. Compute the average waiting time in queue
May 28, 2016
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