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Demand Supply Management for an Industrial Cooler Manufacturer
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School of Science |
Master's thesis
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TU-22
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en
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vii + 68 + liitt. (+3)
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Abstract
Conventional supply chain underlines the material flow from the upstream supplier and towards the downstream customer end.
The companies take advantage of supply chain management to improve cost efficiency.
In recent years, demand chain management is thought to be an approach creating more synergies between customer and supplier.
It originates from the customer end upwards to the supplier.
Nowadays, the demand supply chain management is emphasized to link customer and supplier as a group to create more added-value in the network.
This study examines an industrial cooler manufacturer suffering long-term loss of profit.
The case company failed to address the market trend.
Its products were challenged by other short life cycle products with cheap price.
Moreover, its problematic operational management raises late delivery of shipment and poor quality of products.
The good will of customers and confidence of suppliers are eroded.
To overcome these difficulties, it is necessary to optimize its operational management to improve its core competence.
The scope of this study covers demand and supply management, working process integration and inventory management.
To satisfy the demands of customers with lower costs, production planning and order handling processes are suggested to transform operation from make-to-stock approach to make-to-order approach.
In addition to optimization of demand supply management, work processes and inventory management are scrutinized to improve cost-efficiency.
The result of this study creates a systematic framework of demand supply management for the case company.
The demand plan and production plan serve as the baseline to guide manufacturing activities in the case company.
The operational costs are considerably reduced by minimizing inventory level and work processing time.
Based on this framework, more specific demand and supply management approaches can be further investigated, such as forecast model, economic order quantity and safety stock level for key components.