Management of technological process optimisation

Type of technological equipment	Operations	Distribution law	*Mathematical expectationM(T_P), M(T_F), S*	Mean square deviationS, dispersionΣ²
Manual, linear arrangement	t_p	$f (t_{p}) = \frac{1}{8, 225 \cdot \sqrt{2 \cdot π}} . e^{- \frac{{(t_{p} - 67, 79)}^{2}}{2 \cdot 67, 65}}$	M(t_p)=67.79±8.225	S(t_p) = 8.225 σ² = 67.65
Manual, linear arrangement	t_f	$f (t_{f}) = \frac{1}{14, 12 \cdot \sqrt{2 \cdot π}} . e^{- \frac{{(t_{f} - 82, 02)}^{2}}{2 \cdot 199, 38}}$	M(t_f)=82.02±14.12	S(t_f) = 14.12 σ² = 199.379
Partially automated, linear arrangement	t_p	$f (t_{p}) = \frac{1}{8, 233 \cdot \sqrt{2 \cdot π}} . e^{- \frac{{(t_{p} - 68, 65)}^{2}}{2 \cdot 67, 78}}$	M(t_p)=68.65±8.233	S(t_p) = 8.233 σ² = 67.78
Partially automated, linear arrangement	t_f	$f (t_{f}) = \frac{1}{10, 22 \cdot \sqrt{2 \cdot π}} . e^{- \frac{{(t_{f} - 53, 11)}^{2}}{2 \cdot 104, 44}}$	M(t_f)=53.11±10.22	S(t_f)= 10.219 σ² = 104.438
Partially automated, “tandem” arrangement	t_p	$f (t_{p}) = \frac{1}{4, 431 \cdot \sqrt{2 \cdot π}} . e^{- \frac{{(t_{p} - 36, 84)}^{2}}{2 \cdot 19, 634}}$	M(t_p)=36.84±4.431	S(t_p) = 4.431 σ² = 19.634
Partially automated, “tandem” arrangement	t_f	$f (t_{f}) = \frac{1}{4, 432 \cdot \sqrt{2 \cdot π}} . e^{- \frac{{(t_{f} - 45, 34)}^{2}}{2 \cdot 19, 64}}$	M(t_f)=45.34±4.432	S(t_f) = 4.432 σ² = 19.644
Automatic, “tandem” arrangement	t_p	$f (t_{p}) = \frac{1}{4, 627 \cdot \sqrt{2 \cdot π}} . e^{- \frac{{(t_{p} - 37, 85)}^{2}}{2 \cdot 21, 41}}$	M(t_p)=37.85±4.627	S(t_p) = 4.627 σ² = 21.41
Automatic, “tandem” arrangement	t_f	$f (t_{f}) = \frac{1}{2, 43 \cdot \sqrt{2 \cdot π}} . e^{- \frac{{(t_{f} - 17, 61)}^{2}}{2 \cdot 5, 898}}$	M(t_f)=17.61±2.429	S(t_f) = 2.429 σ² = 5.898
Automatic, “herringbone” arrangement	t_p	$f (t_{p}) = \frac{1}{2, 99 \cdot \sqrt{2 \cdot π}} . e^{- \frac{{(t_{f} - 38, 29)}^{2}}{2 \cdot 8, 926}}$	M(t_p)=38.29±8.926	S(t_p) = 2.987 σ² = 8.926
Automatic, “herringbone” arrangement	t_f	$f (t_{f}) = \frac{1}{0, 48 \cdot \sqrt{2 \cdot π}} . e^{- \frac{{(t_{f} - 10, 1)}^{2}}{2 \cdot 0, 23}}$	M(t_f)=10.1±0.48	S(t_f) = 0.48 σ² = 0.23
Automatic, “parallel” arrangement	t_p	$f (t_{p}) = \frac{1}{3, 94 \cdot \sqrt{2 \cdot π}} . e^{- \frac{{(t_{p} - 31, 09)}^{2}}{2 \cdot 15, 522}}$	M(t_p)=31.09±3.94	S(t_p) = 3.94 σ² = 15.522
Automatic, “parallel” arrangement	t_f	$f (t_{f}) = \frac{1}{0, 904 \cdot \sqrt{2 \cdot π}} . e^{- \frac{{(t_{f} - 10, 94)}^{2}}{2 \cdot 0, 816}}$	M(t_f)=10.94±0.904	S(t_f)= 0,904 σ² = 0.816

Workload of the operator of manual technological equipment

Workload of the operator of partially automated technological equipment

Workload of the operator of automated technological equipment

Dependence of the amount of technological equipment n_am.ed serviced by one operator on the duration t_m of the operation performed immediately on the equipment and without the operator's participation and the correlation of final and preparatory operations t_f/t_p

Diagram of projections for the response surface of a dependence of the amount of equipment n_am.ed serviced by one operator on the performance duration t_m of the operation immediately on the equipment and without the operator's participation and the correlation of final and preparatory operations t_f/t_p

Dependence of the amount of technological equipment n_am.ed serviced by one operator on the duration t_m on of the operation performed immediately on the equipment and without the operator's participation, and on the type of equipment

Interval in the duration of a production line operation to perform the program for 100 products during the time t_m of the operation performed immediately on the equipment and without the participation of the operator

Dependence of the duration of a production line operation to perform the program for 100 products during the time t_m of the operation performed immediately on the equipment and without the participation of the operator, and the correlation t_f/t_p, under: t_f →*min*, t_p→*min*

Dependence of the efficiency of technological equipment on the duration t_m of the operation performed immediately on the equipment and without the participation of the operator, and on the correlation t_f/t_p, under: t_f→*min*, t_p→*min*

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DOI: https://doi.org/10.2478/emj-2020-0022 | Journal eISSN: 2543-912X (formerly 2300-0813) | Journal ISSN: 2543-6597

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Language: English

Page range: 103 - 115

Submitted on: Jan 5, 2020

Accepted on: Jun 30, 2020

Published on: Oct 15, 2020

Published by: Bialystok University of Technology

In partnership with: Paradigm Publishing Services

Keywords:

workload factor,

process productivity,

analytical model,

duration of operations,

amount of equipment

Related subjects:

Business and economics,

Business management,

Industries,

Transportation, logistics, air traffic, shipping,

Engineering,

Mechanical engineering,

Production technology,

Process engineering and industrial engineering

© 2020 Vasyl Lypchuk, Vasyl Dmytriv, published by Bialystok University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 12 (2020): Issue 3 (September 2020)

Management of technological process optimisation

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