The Value of RFID Technology Enabled Information to Manage Perishables

We address the value of RFID technology enabled information to manage perishables in the context of a supplier that sells a random lifetime product subject to stochastic demand and lost sales. The product's lifetime is largely determined by the time and temperature history in the supply chain. We compare two information cases to a Base case in which the product's time and temperature history is unknown and therefore its shelf life is uncertain. In the first information case, the time and temperature history is known and therefore the remaining shelf life is also known at the time of receipt. The second information case builds on the first case such that the supplier now has visibility up the supply chain to know the remaining shelf life of inventory available for replenishment. We formulate these three different cases as Markov decision processes, introduce well performing heuristics of more practical relevance, and evaluate the value of information through an extensive simulation using representative, real world supply chain parameters.simulation;value of information;RFID;perishable inventory

High-global warming potential F-gas emissions in California: comparison of ambient-based versus inventory-based emission estimates, and implications of refined estimates.

To provide information for greenhouse gas reduction policies, the California Air Resources Board (CARB) inventories annual emissions of high-global-warming potential (GWP) fluorinated gases, the fastest growing sector of greenhouse gas (GHG) emissions globally. Baseline 2008 F-gas emissions estimates for selected chlorofluorocarbons (CFC-12), hydrochlorofluorocarbons (HCFC-22), and hydrofluorocarbons (HFC-134a) made with an inventory-based methodology were compared to emissions estimates made by ambient-based measurements. Significant discrepancies were found, with the inventory-based emissions methodology resulting in a systematic 42% under-estimation of CFC-12 emissions from older refrigeration equipment and older vehicles, and a systematic 114% overestimation of emissions for HFC-134a, a refrigerant substitute for phased-out CFCs. Initial, inventory-based estimates for all F-gas emissions had assumed that equipment is no longer in service once it reaches its average lifetime of use. Revised emission estimates using improved models for equipment age at end-of-life, inventories, and leak rates specific to California resulted in F-gas emissions estimates in closer agreement to ambient-based measurements. The discrepancies between inventory-based estimates and ambient-based measurements were reduced from -42% to -6% for CFC-12, and from +114% to +9% for HFC-134a

Methane emissions inventory verification in southern California

Methane (CH4) and carbon monoxide (CO) mixing ratios were measured at an air quality monitoring station near the Mt. Wilson (MW) Observatory in southern California starting in the spring of 2007. Diurnal variation and mixing ratio correlation (R2 = 0.81) were observed. The correlation results observed agree with previous aircraft measurements collected over the greater Los Angeles (LA) metropolitan area. The consistent agreement between CH4 and CO indicates these gases are well-mixed before reaching the sampling site and the emission source contributions of both compounds are reasonably constant. Since CH4 and CO are considered non-reactive on the time scale of dispersion within the LA urban area and their emission sources are likely to be similarly distributed (e.g., associated with human activities) they are subject to similar scales of atmospheric transport and dilution. This behavior allows the relationship of CH4 and CO to be applied for estimation of CH4 emissions using well-documented CO emissions. Applying this relationship a "top-down" CH4 inventory was calculated for LA County based on the measurements observed at MW and compared with the California Air Resources Board (CARB) "bottom-up" CH4 emissions inventory based on the Intergovernmental Panel on Climate Change recommended methodologies. The "top-down" CH4 emissions inventory is approximately one-third greater than CARB's "bottom-up" inventory for LA County. Considering the uncertainties in both methodologies, the different CH4 emissions inventory approaches are in good agreement, although some under and/or uninventoried CH4 sources may exist

Basics of inventory management (Part 6: The (R,s,S)-model)

Inventory Models;management science

Maintenance optimization of a production system with buffercapacity

Marketing;Optimization;produktieleer/ produktieplanning

Locating a bioenergy facility using a hybrid optimization method

In this paper, the optimum location of a bioenergy generation facility for district energy applications is sought. A bioenergy facility usually belongs to a wider system, therefore a holistic approach is adopted to define the location that optimizes the system-wide operational and investment costs. A hybrid optimization method is employed to overcome the limitations posed by the complexity of the optimization problem. The efficiency of the hybrid method is compared to a stochastic (genetic algorithms) and an exact optimization method (Sequential Quadratic Programming). The results confirm that the hybrid optimization method proposed is the most efficient for the specific problem. (C) 2009 Elsevier B.V. All rights reserved

An Evaluation of End of Maintenance Dates and Lifetime Buy Estimations for Electronic Systems Facing Obsolescence

The business of supporting legacy electronic systems is challenging due to mismatches between the system support life and the procurement lives of the systems' constituent components. Legacy electronic systems are threatened with Diminishing Manufacturing Sources and Material Shortages (DMSMS)-type obsolescence, and the extent of their system support lives based on existing replenishable and non-replenishable resources may be unknown. This thesis describes the development of the End of Repair/End of Maintenance (EOR/EOM) model, which is a stochastic discrete-event simulation that follows the life history of a population of parts and cards and operates from time-to-failure distributions that are either user-defined, or synthesized from observed failures to date. The model determines the support life (and support costs) of the system based on existing inventories of spare parts and cards, and optionally harvesting parts from existing cards to further extend the life of the system. The model includes: part inventory segregation, modeling of part inventory degradation and periodic inventory inspections, and design refresh planning. A case study using a real legacy system comprised of 117,000 instances of 70 unique cards and 4.5 million unique parts is presented. The case study was used to evaluate the system support life (and support costs) through a series of different scenarios: obsolete parts with no failure history and never failing, obsolete parts with no failure history but immediately incurring their first failures with and without the use of part harvesting. The case study also includes analyses for recording subsequent EOM and EOR dates, sensitivity analyses for selected design refreshes that maximize system sustainment, and design refresh planning to ensure system sustainment to an end of support date. Lifetime buys refer to buying enough parts from the original manufacturer prior to the part's discontinuance in order to support all forecasted future part needs throughout the system's required support life. This thesis describes the development of the Lifetime Buy (LTB) model, a reverse-application of the EOR/EOM model, that follows the life history of an electronic system and determines the number of spares required to ensure system sustainment. The LTB model can generate optimum lifetime buy quantities of parts that minimizes the total life-cycle cost associated with the estimated lifetime buy quantity