Booking Limit Based Revenue Management Approaches for Customer-Value Oriented Make-to-Order Production

Lohnert, Nina; Fischer, Kathrin

doi:10.1007/978-3-030-29821-0_18

Cited by 5 publications

(4 citation statements)

References 24 publications

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“…Under the incremental manufacturing circumstances of Industry 4.0, it is easy to re-construct a flexible production line with a cyber-physical system to collect various information and realize what and how many product specifications could be customized. To augment the potential scenario, the authors consider that a configuration system under Industry 4.0 should meet the following requirements [8,16,26,27]: (1) Directly collecting and meeting customer dynamic requirements. In a typical procedure, a customer discusses and negotiates through a sales interview and places an order with the assistance of sales office personnel.…”

Section: High-complexity Low-volume Products and Productionmentioning

confidence: 99%

“…authors consider that a configuration system under Industry 4.0 should meet the following requirements [8,16,26,27]: (1) Directly collecting and meeting customer dynamic requirements. In a typical procedure, a customer discusses and negotiates through a sales interview and places an order with the assistance of sales office personnel.…”

Section: High-complexity Low-volume Products and Productionmentioning

confidence: 99%

“…MTO is characterized by back orders with zero inventories as each customer order is unique and cannot be manufactured in advance. Consequently, the main driver in MTO operations is the new transformation under Industry 4.0 about customer orders [26,27]. In view of the various products and changing demand, companies adopt MTO and quick response manufacturing (QRM) strategies to be able to respond quickly to user demand through the quick design and production of products.…”

Section: Introductionmentioning

confidence: 99%

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Developing a Quick Response Product Configuration System under Industry 4.0 Based on Customer Requirement Modelling and Optimization Method

et al. 2019

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In the Industry 4.0 environment, the new manufacturing transformation of mass customization for high-complexity and low-volume production is moving forward. Based on cyber-physical system (CPS) and Internet of things (IoT) technology, the flexible transformation of the manufacturing process to suit diverse customer manufacturing requirements is very possible, with the potential to provide digital “make-to-order” (MTO) services with a quick response time. To achieve this potential, a product configuration system, which translates the voice of customers to technical specifications, is needed. The purpose of this study is to propose a methodology for developing a quick-response product configuration system to enhance the communication between the customer and the manufacturer. The aim is to find an approach to receive requests from customers as inputs and generate a product configuration as outputs that maximizes customer satisfaction. In this approach, engineering characteristics (ECs) are defined, and selection pools are initially constructed. Then, quality function deployment (QFD) is modified and integrated with the Kano model to qualitatively and quantitatively analyze the relationship between customer requirements (CRs) and customer satisfaction (CS). Next, a mathematical programming model is applied to maximize the overall customer satisfaction level and recommend an optimal product configuration. Finally, sensitivity analysis is conducted to suggest revisions for customers and determine the final customized product specification. A case study and an OrderAssistant system are implemented to demonstrate the procedure and effectiveness of the proposed quick response product configuration system.

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Section: High-complexity Low-volume Products and Productionmentioning

confidence: 99%

Section: High-complexity Low-volume Products and Productionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Developing a Quick Response Product Configuration System under Industry 4.0 Based on Customer Requirement Modelling and Optimization Method

et al. 2019

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“…Currently, most enterprises have adopted an order-oriented production model to better satisfy the diverse needs of the market and customers [1], [2]. For this, enterprises must completely evaluate the production capacity of their workshops, comprehensively consider the specific requirements of each customer, and reasonably manage production to reduce costs and enhance their competitiveness.…”

Section: Introductionmentioning

confidence: 99%

Permutation Flow Shop Scheduling Optimization Method Based on Cooperative Games

Zhang

Guo

2023

IEEE Access

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This paper proposes a cooperative games model for the permutation flow shop scheduling problem (PFSP) with multiple customer tasks. Here, customers create alliances through cooperation in the case of delayed and early delivery penalty constraints, and tasks in the alliance are rescheduled to seek maximum cost savings. A new β rule allocation method is proposed considering the variability in the delay penalty factor of different ordered tasks. Additionally, it is proven that the cost-saving allocation resulting from this allocation method is a core allocation of the PFSP cooperative games. A hybrid particle swarm optimization algorithm is proposed to obtain the optimal scheduling of each coalition. The algorithm uses a particle swarm as the main body, maintains the advantage of fast convergence of particle swarm optimization, increases the diversity among the population, and improves the optimization performance of the algorithm. Finally, the effectiveness of the algorithm, model, and allocation method is verified via experiments. The total cost for all customers under the optimal scheduling sequence is 5595.8, compared to 6689.8 for the initial scheduling order. The proposed cooperative games model can be applied to various enterprises to better satisfy the diverse needs of the market and customers.

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Bid-Preis gesteuerte Auftragsannahme in der Make-to-Order-Produktion unter Berücksichtigung von Kundenwertigkeiten

Lohnert

Fischer

2021

Logistik in Wissenschaft Und Praxis

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Booking Limit Based Revenue Management Approaches for Customer-Value Oriented Make-to-Order Production

Cited by 5 publications

References 24 publications

Developing a Quick Response Product Configuration System under Industry 4.0 Based on Customer Requirement Modelling and Optimization Method

Developing a Quick Response Product Configuration System under Industry 4.0 Based on Customer Requirement Modelling and Optimization Method

Permutation Flow Shop Scheduling Optimization Method Based on Cooperative Games

Bid-Preis gesteuerte Auftragsannahme in der Make-to-Order-Produktion unter Berücksichtigung von Kundenwertigkeiten

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