Details
| Original language | English |
|---|---|
| Pages (from-to) | 516-521 |
| Number of pages | 6 |
| Journal | Procedia CIRP |
| Volume | 67 |
| Early online date | 21 Mar 2018 |
| Publication status | Published - 2018 |
| Event | 11th CIRP International Conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME 2017 - Ischia, Naples, Italy Duration: 19 Jul 2017 → 21 Jul 2017 |
Abstract
Sales revenues of small and medium-sized enterprises are subject to seasonal fluctuation. This leads often to overloaded or underutilized manufacturing resources. Either way, this results in revenue losses. Therefore, companies have to optimize their resource utilization. This paper describes a new methodology for a dynamic bid price system by using correlations of revenue management in production planning to level the resource utilization. The methodology supports especially small and medium-sized enterprises, which are often affected by additional work shifts across seasons. Furthermore, the proposed method points out dependencies between costs and capacity to avoid financial losses. The method has been developed and is being tested in collaboration with two small and medium-sized enterprises.
Keywords
- Dynamic Bid Price, Manufacturing Resource Utilization, Production Planning
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Engineering(all)
- Industrial and Manufacturing Engineering
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In: Procedia CIRP, Vol. 67, 2018, p. 516-521.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Dynamic bid pricing for an optimized resource utilization in small and medium sized enterprises
AU - Denkena, Berend
AU - Dittrich, Marc André
AU - Stamm, Siebo
N1 - Funding information: The authors thank the Federal Ministry of Education and Research of Germany (BMBF) for its financial and organizational support of the project ‘‘Dynamic capacity planning and control in manufacturing SMEs’’ (project ‘‘KaPro’’, 02P15K563).
PY - 2018
Y1 - 2018
N2 - Sales revenues of small and medium-sized enterprises are subject to seasonal fluctuation. This leads often to overloaded or underutilized manufacturing resources. Either way, this results in revenue losses. Therefore, companies have to optimize their resource utilization. This paper describes a new methodology for a dynamic bid price system by using correlations of revenue management in production planning to level the resource utilization. The methodology supports especially small and medium-sized enterprises, which are often affected by additional work shifts across seasons. Furthermore, the proposed method points out dependencies between costs and capacity to avoid financial losses. The method has been developed and is being tested in collaboration with two small and medium-sized enterprises.
AB - Sales revenues of small and medium-sized enterprises are subject to seasonal fluctuation. This leads often to overloaded or underutilized manufacturing resources. Either way, this results in revenue losses. Therefore, companies have to optimize their resource utilization. This paper describes a new methodology for a dynamic bid price system by using correlations of revenue management in production planning to level the resource utilization. The methodology supports especially small and medium-sized enterprises, which are often affected by additional work shifts across seasons. Furthermore, the proposed method points out dependencies between costs and capacity to avoid financial losses. The method has been developed and is being tested in collaboration with two small and medium-sized enterprises.
KW - Dynamic Bid Price
KW - Manufacturing Resource Utilization
KW - Production Planning
UR - http://www.scopus.com/inward/record.url?scp=85044622446&partnerID=8YFLogxK
U2 - 10.1016/j.procir.2017.12.254
DO - 10.1016/j.procir.2017.12.254
M3 - Conference article
AN - SCOPUS:85044622446
VL - 67
SP - 516
EP - 521
JO - Procedia CIRP
JF - Procedia CIRP
SN - 2212-8271
T2 - 11th CIRP International Conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME 2017
Y2 - 19 July 2017 through 21 July 2017
ER -