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Abstract
With the emergence of individualised and personalised customer demands, the interaction of service and product has come into the sight of manufacturers and thus promoted the arising of service-oriented manufacturing (SOM), a new business mode that combines manufacturing and service. Be similar to the conventional manufacturing, the customer demand prediction (CDP) of SOM is very important since it is the foundation of the following manufacturing stages. As there are always tight and frequent interactions between service providers and customers in SOM, the customer satisfaction would significantly influence the customer demand of the following purchasing periods. To cope with this issue, a novel CDP approach for SOM incorporating customer satisfaction is proposed. Firstly, the structural relationships among customer satisfaction index and the influence factors are quantitatively modelled by using the structural equation model. Secondly, to reduce the adverse effect of multiple structural input data and small sample size, the least square support vector mechanism is employed to predict customer demand. Finally, the CDP of the air conditioner compressor which is a typical SOM product is implemented as the real-case example, and the effectiveness and validity of the proposed approach is elaborated from the prediction results analysis and comparison.
Acknowledgement
The authors express sincere appreciation to the designers and engineers for their support in collecting the customer requirements data and establishing the quality function deployment, and also express sincere appreciation to the anonymous referees for their helpful comments to improve the quality of the paper.
Disclosure statement
No potential conflict of interest was reported by the authors.