Reverse Blending: An economically efficient approach to the challenge of fertilizer mass customization

Benhamou, Latifa; Giard, Vincent; Khouloud, Mehdi; Fenies, Pierres; Fontane, Frédéric

doi:10.1016/j.ijpe.2019.107603

Cited by 9 publications

(13 citation statements)

References 44 publications

(45 reference statements)

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“…Customers are the core of the MC process. They can put forward personalized product demands according to their will and can participate in product design and manufacturing [21,22].…”

Section: A Overview Of MCmentioning

confidence: 99%

Mass Customization-Oriented Customer Demand Response Service Platform Based on Cloud Computing and Internet of Things

Hong-yi

Fan

2022

IEEE Access

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The purpose is to establish Mass Customization (MC)-oriented Customer Demand Response (CDR) service platform based on Cloud Computing (CC) and the Internet of Things (IoT). Firstly, the MCoriented Demand Response (DR) process and the characteristics of CC are analyzed. Secondly, an MCoriented CDR service platform system based on CC and IoT is proposed. Finally, the edge-cloud collaborative computing method is used to maintain the efficiency and stability of the CC platform, and the proposed method is compared with other state-of-art algorithms to further prove its effectiveness. The results show that the parameters φ and V have a significant impact on the queue size and operation cost. Compared with other methods, the operation cost of the proposed edge-cloud collaborative computing method is relatively low. Thus, the proposed edge-cloud collaborative computing method is more applicable in high-speed and low-speed data; it can also improve the resource utilization of the Data Center (DC) and reduce the operation cost. The research results provide a basis for the establishment of the MCoriented CDR service platform.

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“…Customers are the core of the MC process. They can put forward personalized product demands according to their will and can participate in product design and manufacturing [21,22].…”

Section: A Overview Of MCmentioning

confidence: 99%

Mass Customization-Oriented Customer Demand Response Service Platform Based on Cloud Computing and Internet of Things

Hong-yi

Fan

2022

IEEE Access

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“…In this research, the assigning of products for the production model is based on the percentage of components as developed based on the previous work of Benhamou et al [1]. This approach has been upgraded by taking the profit from each product into account.…”

Section: Figure 1: Planning Periodmentioning

confidence: 99%

“…In the second stage, the random probability of events exists, so then the number of materials for producing products is considered the decision variable used to minimize the total cost for manufacturing, inventory, and penalty. According to Benhamou et al [1], a varying type of fertilizer exists to meet with customer demand. The increase in the number of fertilizer formulae leads to an increase in inventory, transportation, and production.…”

Section: Literature Reviewmentioning

confidence: 99%

Two-Stage Production Planning Under Stochastic Demand: Case Study of Fertilizer Manufacturing

Wang¹,

Syu²,

Chou³

et al. 2022

Computers, Materials &Amp; Continua

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Agriculture is a key facilitator of economic prosperity and nourishes the huge global population. To achieve sustainable agriculture, several factors should be considered, such as increasing nutrient and water efficiency and/or improving soil health and quality. Using fertilizer is one of the fastest and easiest ways to improve the quality of nutrients inland and increase the effectiveness of crop yields. Fertilizer supplies most of the necessary nutrients for plants, and it is estimated that at least 30%-50% of crop yields is attributable to commercial fertilizer nutrient inputs. Fertilizer is always a major concern in achieving sustainable and efficient agriculture. Applying reasonable and customized fertilizers will require a significant increase in the number of formulae, involving increasing costs and the accurate forecasting of the right time to apply the suitable formulae. An alternative solution is given by two-stage production planning under stochastic demand, which divides a planning schedule into two stages. The primary stage has non-existing demand information, the inputs of which are the proportion of raw materials needed for producing fertilizer products, the cost for purchasing materials, and the production cost. The total quantity of purchased material and produced products to be used in the blending process must be defined to meet as small as possible a paid cost. At the second stage, demand appears under multiple scenarios and their respective possibilities. This stage will provide a solution for each occurring scenario to achieve the best profit. The two-stage approach is presented in this paper, the mathematical model of which is based on linear integer programming. Considering the diversity of fertilizer types, the mathematical model can advise manufacturers about which products will generate as much as profit as possible. Specifically, two objectives are taken into account. First, the paper's thesis focuses on minimizing overall system costs, e.g., including inventory cost, purchasing cost, unit cost, and ordering cost at Stage 1. Second, the thesis

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“…To achieve a wide variety of customized fertilizers, RB seeks the optimal chemical specifications of the smallest set, called "canonical base (CB)", of blending inputs, called "Canonical Basis Inputs (CBIs)", whose blend combinations form a bill of materials (BOM) used to produce any quantity of any output belonging to the variety of fertilizers under consideration [8]. Other additional fertilizer formulae may be obtained from these CBIs by a classical blending linear problem aiming at minimizing deviations from the specifications of these formulae.…”

Section: Reverse Blending Fundamentalsmentioning

confidence: 99%

“…packaging in the coffee industry [6] or product shape/cutting in the steel industry [7]). We hold the view that in the process industry, Reverse Blending (RB) (an extension of classical blending where the inputs are to be defined), can be a disruptive approach to implementing effective delayed differentiation by adding to mere packaging a dimension concerning actual product internal composition [8]. By showing a major impact on Supply Chain (SC) organization, our paper discusses the potential benefits of RB for those fertilizer producers who are prepared to redesign their supply chain.…”

Section: Introductionmentioning

confidence: 99%

Potential Benefits of Reverse Blending in the Fertilizer Industry

Benhamou¹,

Fenies²,

Giard³

2020

IFIP Advances in Information and Communication Technology

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Delayed differentiation, one of the key techniques of mass customization, has proven to be a high-performance strategy in the discrete industry. In the process industry, however, it remains poorly explored, especially when differentiation relates to product composition rather than form. Reverse Blending is a new OR blending problem based on a quadratic formulation, where output requirements are similar to those of classical blending, but here inputs are not preexisting and must be defined simultaneously with their use in the blending process while exactly meeting output requirements. These may then be used to obtain a wide variety of custom fertilizers (outputs) from a small number of Canonical Basis Inputs that can be blended outside the chemical plant, close to the endusers. This would avoid production of a wide variety of small batches of final products through a small number of large batches of intermediate products, resulting in valuable logistical streamlining and substantial cost savings. Accordingly, our paper investigates the potential benefits of implementing Reverse Blending in the fertilizer industry.

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Reverse Blending: An economically efficient approach to the challenge of fertilizer mass customization

Cited by 9 publications

References 44 publications

Mass Customization-Oriented Customer Demand Response Service Platform Based on Cloud Computing and Internet of Things

Mass Customization-Oriented Customer Demand Response Service Platform Based on Cloud Computing and Internet of Things

Two-Stage Production Planning Under Stochastic Demand: Case Study of Fertilizer Manufacturing

Potential Benefits of Reverse Blending in the Fertilizer Industry

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