Introduction to Part Supply
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Part Supply sentence examples within Spare Part Supply
3D printing or additive manufacturing (AM) (in the industrial context) is an innovative, as opposed to subtractive, technology, bringing new opportunities and benefits to the spare part supply chain (SPSC).
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First, we simulate the spare part supply chain to show the impact of the spare part service measures on the time to repair distribution.
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Part Supply sentence examples within part supply chain
3D printing or additive manufacturing (AM) (in the industrial context) is an innovative, as opposed to subtractive, technology, bringing new opportunities and benefits to the spare part supply chain (SPSC).
Full Text
First, we simulate the spare part supply chain to show the impact of the spare part service measures on the time to repair distribution.
Full Text
3D printing or additive manufacturing (AM) (in the industrial context) is an innovative, as opposed to subtractive, technology, bringing new opportunities and benefits to the spare part supply chain (SPSC).
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This paper aims at providing an effective solution method for a real-world energy-efficient part supply scheduling problem (EPSSP) between the central receiving store and supermarkets with electric transport device on purpose of coordinating production and transportation in the automobile industry.
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The main barriers for remanufacturing business are the possibility for cannibalizing new mobile phones' market share, the uncertainty of core supply, discontinuity of replacement part supply, lack of product knowledge among consumers and retailers, hesitation of retailers to sell remanufactured products, and lack of strict and clear regulations about remanufacturing business.
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It is found that when the mismatch between warranty demand and part supply is higher, firms can enjoy more significant cost savings.
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When a disruption occurs because of a delayed part supply, a quality problem or an operator absence, a reactive scheduling approach should be used in a short time in order to prevent significant deviations in final performances.
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In modern production systems, an ever-rising product variety has imposed great challenges for in-plant part supply systems used to feed mixed-model assembly lines with required parts.
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First, we simulate the spare part supply chain to show the impact of the spare part service measures on the time to repair distribution.
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The identification of parts is essential for the efficient automation of logistic processes such as part supply in assembly and disassembly.
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Equipments monitored by sensors as well as the transmission of sensors data to the spare part supply chain represent an interesting venue for dealing with this contemporaneous industrial challenge.
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Based on the idea of chaotic mapping and reverse learning, the food source coding and initialization were redesigned, and a modified discrete artificial bee colony algorithm was constructed to make joint decision on part supply time and delivery quantity.
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The swirler is placed in an annular part supplying the oxidant flow and the central pipe delivers radially a fuel through eight holes symmetrically distributed on the periphery of the tube.
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