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  • In the presented article, we describe a general procedure to solve the problem of how many employees there should be in a workplace so that the time to get the necessary work done didn't exceed a desired level, or more precisely, that the probability of the work lasting too long was considerably low. We outline our procedure on the assumption that historical data of process cycle times for different amounts of work and a given daily number of employees are available. Further, we assume the times always follow a Gamma distribution, and the employees are equally productive. To derive the procedure, unconditional and conditional expected values and variances are used to estimate parameters of various Gamma distributions, relating behaviour of process cycle times to different daily numbers of employees.
  • In the presented article, we describe a general procedure to solve the problem of how many employees there should be in a workplace so that the time to get the necessary work done didn't exceed a desired level, or more precisely, that the probability of the work lasting too long was considerably low. We outline our procedure on the assumption that historical data of process cycle times for different amounts of work and a given daily number of employees are available. Further, we assume the times always follow a Gamma distribution, and the employees are equally productive. To derive the procedure, unconditional and conditional expected values and variances are used to estimate parameters of various Gamma distributions, relating behaviour of process cycle times to different daily numbers of employees. (en)
Title
  • Stochastic Control of Process Times based on Working Performance
  • Stochastic Control of Process Times based on Working Performance (en)
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  • Stochastic Control of Process Times based on Working Performance
  • Stochastic Control of Process Times based on Working Performance (en)
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  • RIV/47813059:19520/13:#0002200!RIV14-MSM-19520___
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  • I
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  • 108021
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  • RIV/47813059:19520/13:#0002200
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  • Model; work shift; expected value; variance; number of workers (en)
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  • [83A180368E6B]
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  • Brno
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  • Brno
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  • Sborník 22.ročníku mezinárodní konference metalurgie a materiálů Metal 2013
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  • TOŠENOVSKÝ, Filip
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  • TANGER spol. s r.o.
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  • 978-80-87294-39-0
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  • 19520
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