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Production planning and scheduling for companies with divergent processes, where a single component can be transformed into several finished products, are challenging as planners might face material misallocation issues. In this paper, we address the problem of managing a divergent process with DDMRP stock buffers, where different finished products are bottled with the same component having a fixed batch size. An allocation decision needs to be made to determine the quantities of finished products to be bottled. This study is motivated by a real-life problem faced by a dermo-cosmetic company. We compare and analyze by simulation nine different policies triggering allocation decisions. The first policy is the classic DDMRP rule, while the others are new policies, including a virtual buffer of a generic finished product and ConWIP loops, delaying the allocation decision. Our results show that the policy combining the classic DDMRP rule and a ConWIP loop surrounding a part of the process reduces the work-in-process by 34% compared to the classic DDMRP while ensuring high customer service rates and control of flow times. [ABSTRACT FROM AUTHOR]

Like Kanban or classic inventory management, Demand Driven Material Requirements Planning (DDMRP) assumes that an order is created when the stock level drops below a given level. The assessment of this level can be continuous or periodic. A periodic evaluation can force better repartition of the load over time. DDMRP characterizes the demand for a product by its average daily demand. This aggregation specifies neither the average size of the elementary demands nor the average duration between two elementary demands. Based on a discrete event simulation model, this study suggests that, at least for a flow-shop organization, the DDMRP method, with continuous order generation, is suitable for large mean time between elementary orders, while periodic observation improves the method for small values of it. [ABSTRACT FROM AUTHOR]

Demand Driven Material Requirements Planning (DDMRP) is a recent method mixing push and pull flow management. Although it claims to be the solution to traditional methods' limitations, the DDMRP method works at infinite capacity: manufacturing or supply orders are launched according to a logic of replenishment of stocks defined as buffers. This article proposes an evaluation of capacity management using visual charts developed by simulation. These charts correlate the bottleneck resource's loading rate to a service rate by considering one of the DDMRP method parameters, the Decoupled Lead Time (DLT). The charts are a decision support tool. They allow identifying to which loading rate the DLTs are representative of the flow times of manufacturing orders and which capacity level to use. We study different workshops, including a real industrial case. Our results show that it is better to control the flow times by adjusting capacity rather than adjust the DLT parameter. [ABSTRACT FROM AUTHOR]

To meet the challenge of feeding almost 10 billion people by 2050, wheat yield has to double by 2050. However, over the past 20 years, yield increase has slowed down and even stagnated in the main producing countries. Following the example of maize, hybrids have been suggested as a solution to overcome yield stagnation in wheat. However, wheat heterosis is still limited and poorly understood. Gaining a better understanding of hybrid vigor holds the key to breed for better varieties. To this aim, we have developed and phenotyped for physiological and agronomic traits an incomplete factorial design consisting of 91 hybrids and their nineteen female and sixteen male parents. Monitoring the plant development with normalized difference vegetation index revealed that 89% of the hybrids including the five higher yielding hybrids had a longer grain filling phase with a delayed senescence that results in larger grain size. This average increase of 7.7% in thousand kernel weight translated to a positive mid-parent heterosis for grain yield for 86% of hybrids. In addition, hybrids displayed a positive grain protein deviation leading to a +4.7% heterosis in protein yield. These results shed light on the physiological bases underlying yield heterosis in wheat, paving new ways to breed for better wheat hybrids.

Push and pull methods have been adopted for specific volume production and uncertainty scenarios in order to plan and control production. The further development of hybrid or integrated methods allows benefit to be drawn from opposing approaches. The literature concerning Demand-Driven Material Requirements Planning (DDMRP) proves its superiority under conditions of internal and external uncertainty for high-volume production compared to the most implemented push method (manufacturing requirements planning MRPII). Companies that have adopted this method, manufacture on average 10–15 parts per product, with 2 or 3 levels of bills of materials. In this paper, we evaluate the applicability of DDMRP in a complex manufacturing environment (e.g. products of four levels of bill of materials) in terms of customer satisfaction and stock levels. Buffered and non-buffered items clustered in seven types of decoupling structures contributed to this complexity. We developed a DDMRP model for planning and execution purposes, which was simulated in ARENA's discrete events software. We analysed the model's on-hand stock and delayed orders. DDMRP works effectively under the manufacturing conditions considered. It is found to prevent inventory stockouts and overstocks, reduce lead time by 41% and reduce stock levels by 18%. The success of this method; however, depends on the strategic positioning of the buffers. [ABSTRACT FROM AUTHOR]