scholarly journals Demand forecasting procedure for short life-cycle products with an actual food processing enterprise

2014 ◽  
Vol 7 (sup2) ◽  
pp. 85-92 ◽  
Author(s):  
Rie Gaku
2016 ◽  
Vol 55 (8) ◽  
pp. 2336-2350 ◽  
Author(s):  
Mario José Basallo-Triana ◽  
Jesús Andrés Rodríguez-Sarasty ◽  
Hernán Darío Benitez-Restrepo

Author(s):  
Jinju Kim ◽  
Harrison Kim

AbstractShort-life cycle products are frequently replaced and discarded despite being resource-intensive. The short life span and the low utilization rate of the end-of-life products cause severe environmental problems and waste of resources. In the case of short-life cycle products, a new generation of products is released sooner than other products, therefore there are the opportunities to have various generations of products during the remanufacturing process. The commonality between generations increases the intergenerational component compatibility, which increases the efficiency of the manufacturing and remanufacturing processes, while at the same time weakening the performance difference between generations. This paper proposes a mathematical model to investigate the effect of commonality among generations on the overall production process. Based on various given new generation product designs with different commonality, we aim to propose optimal production planning and pricing strategies to maximize the total profitability and investigate how the results vary according to the commonality strategies between product generations.


2020 ◽  
Vol 26 (4) ◽  
pp. 3106-3122
Author(s):  
Peipei Liu

Accurate demand forecasting is always critical to supply chain management. However, many uncertain factors in the market make this issue a huge challenge. Especially during the current COVID-19 outbreak, the shortage of certain types of medical consumables has become a global problem. The intermittent demand forecast of medical consumables with a short life cycle brings some new challenges, such as the demand occurring randomly in many time periods with zero demand. In this research, a seasonal adjustment method is introduced to deal with seasonal influences, and a dynamic neural network model with optimized model selection procedure and an appropriate model selection criterion are introduced as the main forecasting models. In addition, in order to reduce the impact of zero demand, it adds some input nodes to the neural network by preprocessing the original input data. Lastly, a modified error measurement method is proposed for performance evaluation. Experimental results show that the proposed forecasting framework is superior to other intermittent demand models.


2020 ◽  
Vol 142 (12) ◽  
Author(s):  
Jinju Kim ◽  
Harrison M. Kim

Abstract Short life cycle products are frequently replaced and discarded, even though they are resource-intensive products. Technological advances and rapid changes in demand have led manufacturers to develop their innovative next-generation products quickly, which not only enables multiple generations to coexist in the market but also speeds up the technological obsolescence of products. Diversity of collected end-of-life (EoL) and rapid technological obsolescence make the effective recovery of EoL products difficult. The low utilization rate of EoL products causes serious environmental problems such as e-waste and waste of natural resources. To deal with the conflict between the technical evolution of products and the promotion of social benefits in solving environmental problems, this paper focuses on the impact of generational commonality effects on the overall production process including manufacturing and remanufacturing. Generational commonality leads to an increase in the efficiency of manufacturing due to reducing related costs. Additionally, from the remanufacturing perspective, the interchangeability between generations can help collect the EoL products needed for remanufacturing. On the other hand, it causes a weakening of the level of performance and technology evolution between generations that significantly affect the demand for short life cycle products. Therefore, this study identifies these trade-offs of generational commonality levels in both manufacturing and remanufacturing based on a quantitative approach. This study finds how different pricing strategies, production plans, and recovery costs are based on the designs of a new generation with a different degree of generational commonality.


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