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Alternative Logistic Management Policies

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Literature is reviewed in support of a study that will assess the effectiveness of alternative logistics management policies to assure the attainment of required levels of product quality in small manufacturing firms. Literature is reviewed in the following topical areas of interest:

Supply-chain management plays a central role in the management of an organizationĘs value-chain. Essential to the effectiveness of an organizationĘs supply-chain management are the concepts and procedures associated with cycle-time reduction and just-in-time resource management (Sharland, Eltantawy, & Giunipero, 2003). Cycle-time reduction and just-in-time resource management are most frequently associated with manufacturing operations. In fact, however, these elements of supply chain management are equally relevant in a variety of operational contexts (Delattre, 2005). Similarly, just-in-time concepts are applicable to functions other than inventory management.

Waste, considered in the context of managing production operations, refers to any activity that detracts from the creation of value. In the current environment of global business operations, competitive advantages derive in large part from the integration and coordination of the various activities of the value chain. In such an environment, it is important to reduce total costs as well as design, production, and distribution times (Nichols, 2003).

. . .
ign changes to existing process (redesign) Create new processes (development) Control Implement process changes (application) Monitor progress (verification) The goal of the program at General Electric is to minimize process defects. The goal in relation to a supply-chain management program at a company, as an example, would be to reduce the levels of inefficiency in the process. While the ultimate goal is zero-defects, the Six-Sigma target at General Electric for any process is a maximum of 3.4 defects per million opportunities. The target for any specific company will be determined by the needs and characteristics of the supply-chain management process at that company (Brewer & Higme, 2005). The bases for Six-Sigma analysis and control are probability and tolerances related to the area under the normal curve. The tolerance band is ¦6*s = 12*s = 12*10 = 120 units wide. The probability density function (PDF) curves can shift either right or left by (1/4)*(120/2) = 15 units. This level would place the shifted X-bar at 85 or 115 when at the extremes. The objective is to keep the process cantered (Dick, 2005). When the curve is shifted to the left by 1.5*s, the left tail of the curve is cut at the Z-score of (6-1.5) = 4.5 wher
. . .

Some common words found in the essay are:
Prasad Thorn, Eltantawy Giunipero, Brewer Higme, Becerra Greene, Just-in-Time JIT, Carter Ellram, Stevenson Barnes, Standards Organization, Market Reporter, Esper Williams, iso 9000, supply-chain management, tata prasad, quality assurance, prasad thorn, prasad thorn 1999, thorn 1999, tata prasad thorn, iso 9000 certification, 9000 certification, supply chain, six-sigma program, chain management, supply chain management, stevenson barnes 2001,
Approximate Word count = 5433
Approximate Pages = 22 (250 words per page)

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