Capacity reservation and utilization for a manufacturer with uncertain capacity and demand

We consider an OEM (Original Equipment Manufacturer) that has outsourced the production activities to a CM (Contract Manufacturer). The CM produces on a non-dedicated capacitated production line, i.e., the CM produces for multiple OEMs on the same production line. The CM requires that all OEMs reserve capacity slots before ordering and responds to these reservations by acceptance or partial rejection, based on allocation rules that are unknown to the OEM. Therefore, the allocated capacity for the OEM is not known in advance, also because the OEM has no information about the reservations of the other OEMs. We study this problem from the OEM's perspective who faces stochastic demand and stochastic capacity allocation from the contract manufacturer. A single-item periodic review inventory system is considered and we assume linear inventory holding, backorder, and reservation costs. We develop a stochastic dynamic programming model for this problem and characterize the optimal policy. We conduct a numerical study where we also consider the case that the capacity allocation is dependent on the demand distribution. For this case, we show the structure of the optimal policy based on a numerical study. Further, the numerical results reveal several interesting managerial insights, such as the optimal reservation policy is being little sensitive to the uncertainty of capacity allocation. In that case, the optimal reservation quantities hardly increase, but the optimal policy suggests increasing the utilization of the allocated capacity. Moreover, we show that for the contract manufacturer, to achieve the desired behavior, charging small reservation costs is sufficient

THE SEATED-SINGLE-ARM-ROW AS A POST-ACTIVATION POTENTIATION EXERCISE TO ENHANCE POWER OUTPUT DURING KAYAKING ON AN ERGOMETER

This study investigated if the seated-single-arm-row (SSAR) could be used as a post-activation-potentiation-exercise (PAPE) during warm up to induce enhanced power output during kayaking on an ergometer. Ten well-trained kayakers (4 females, 6 males) performed three repetitions of the SSAR at 91% one-repetition maximum as the PAPE. Participants were assessed for their peak and average power output while performing 14 maximal effort strokes on a kayak ergometer; to simulate a race start; with versus without PAPE as a warm up, at three-minute intervals up to 18 minutes. Mean peak power with PAPE was found to be approximately 6% higher (1172.5 vs 1106.8 W) compared with no PAPE, t(9)=2.61, p=0.03. No differences in mean average power were found. Six out of the 10 kayakers registered higher mean peak and average power in one of their experimental trials compared with their control trial. These kayakers could be positive responders to PAPE. The SSAR performed during warm up enabled kayakers to increase their peak power output when paddling on an ergometer, but did not result in higher average power output. The utility of the SSAR as a PAPE to enhance overall power output when paddling on an ergometer, with the perspective of applying this technique to enhance performance during on-water kayaking, requires further investigation

The Transverse Particle Migration of Highly Filled Polymer Fluid Flow in a Pipe

Shear-induced particle migration was investigated by using a continuum diffusive -flux model for the creep flow of nickel powder filled polymers, which are viscous with shear-thinning characteristic. The model, together with flow equations, was employed for solving the non-Newtonian flow patterns and non-uniform particle concentration distribution of mono-modal suspensions in a pressure-driven tube flow. Particle volume fraction and velocity fields for the non-homogenous shear flow field were predicted for 40% particle volume fraction. The model captures the trends found in experimental investigations.Singapore-MIT Alliance (SMA

Effect of carbon emission regulations on transport mode selection under stochastic demand

Companies are expiriencing new and more important reasons to pay attention to their carbon footprint. In this work we consider a 'carbon-aware' company (either by choice or enforced by regulation) that is reconsidering the transport mode selection decsion. Traditionally the trade-off has been between lead time (and corresponding inventory costs) and unit transportation cost but now emission costs come into the equation. We use a carbon emission measurement methodology based on real-life data and incorporate it into an inventory model. We consider the results for different types of emission regulation (including voluntary targets). We find that even though large emission reductions can be obtained by switching to a different mode, the actual decision depends on the regulation and other practical issues

Effect of carbon emission regulations on transport mode selection in supply chains

Policy-makers are developing regulation mechanisms to drive down carbon emis- sions resulting from among others transport. We investigate what the effect of two regulation mechanisms is on the transport mode selection decision. We analyze the situation in which a single transport mode is to be selected by a decision-maker to conduct all transport (for one item). A faster transport mode typically results in lower inventory (or a higher service) at the cost of higher emissions and transport costs. We consider two possible emission regulation alternatives: an emission cost and an emission constraint. We use an accurate calculation method to determine the carbon emissions and incorporate them explicitly in our model. Our results show that the emission cost is only a small part of the total cost and we conclude that introducing an emission cost for freight transport via a direct emission tax or a market mechanism such as cap and trade are not likely to result in significant changes in transport modes and hence will not result in a large reduction of emis- sions. If policy-makers aim to reduce carbon emissions by a large fraction, they should implement a constraint on freight transport emissions

Effect of carbon emission regulations on transport mode selection under stochastic demand

Companies are expiriencing new and more important reasons to pay attention to their carbon footprint. In this work we consider a 'carbon-aware' company (either by choice or enforced by regulation) that is reconsidering the transport mode selection decsion. Traditionally the trade-off has been between lead time (and corresponding inventory costs) and unit transportation cost but now emission costs come into the equation. We use a carbon emission measurement methodology based on real-life data and incorporate it into an inventory model. We consider the results for different types of emission regulation (including voluntary targets). We find that even though large emission reductions can be obtained by switching to a different mode, the actual decision depends on the regulation and other practical issues

Switching transport modes to meet voluntary carbon emission targets

The transport sector is the second largest carbon emissions contributor in Europe and its emissions continue to increase. Many shippers are committing themselves to reducing transport emissions voluntarily, possibly in anticipation of increasing transport prices. In this paper we study a shipper that has outsourced transport and has decided to cap its carbon emissions from outbound logistics for a group of products. Setting an emission constraint for a group of products allows taking advantage of reducing emissions substantially where it is less costly and less where it is more costly. We focus on reducing emissions by switching transport modes within an existing network, since this has a large impact on emissions. In addition, the company sets the sales prices for the products, which in uences demand. We develop a solution procedure that uses Lagrange relaxation. Conditions on total logistics cost and unit emissions are derived determine which transport mode is selected for a product. It is observed that a diminishing rate of return applies in reducing emissions by switching transport modes. In a case study we apply our method to a producer of bulk liquids and find that emissions can be reduced by 10% at only a 0.7% increase in total logistics cost. Keywords: carbon emissions, green supply chains, sustainability, transport mode selection, Lagrange relaxation, pricing

Inventory management with advance capacity information

One of the important aspects of supply chain management is dealing with demand and supply uncertainty. The uncertainty of future supply can be reduced, if a company is able to obtain advance capacity information (ACI) on future supply/production capacity availability from its supplier. We address a periodic-review inventory system under stochastic demand and stochastic limited supply, for which ACI is available. We show that the optimal ordering policy is a state-dependent base stock policy characterized by a base stock level that is a function of ACI. We establish a link to inventory models using advance demand information (ADI) by developing a capacitated inventory system with ADI, and showing that the model is closely related to the proposed ACI model. Our numerical results reveal several managerial insights. In particular, we show that ACI is most beneficial when there exists sufficient flexibility to react to anticipated demand and supply capacity mismatches. Further, most of the benefits can be reached with only limited future visibility. We also show that the system parameters affecting the value of ACI interact in a complex way, and therefore need to be considered in an integrated manner

A steady-state Bi-substrate technique for measurement of the thermal conductivity of ceramic coatings

This paper presents a steady-state, bi-substrate technique for measurement of the through-thickness thermal conductivity of ceramic coatings, with a range of specimen thickness and porosity content. The technique is based on establishing unidirectional steady-state heat flow through the sample, sandwiched between a pair of (metallic) substrates with known thermal properties. Comparison between the heat fluxes passing through the two substrates allows a check to be made about the accuracy of the assumption of unidirectional heat flow. The interfacial conductances must be known and these can be estimated by testing samples of different thickness. Measured conductivities are likely to be more accurate if the interfacial conductance is relatively high. This is assisted by the introduction of a thin interfacial layer of a viscous, thermally conductive compound, or thermal pads of some sort, and by maintaining a suitable pressure across the setup. However, if such compounds (pastes) are used, then care must be taken to ensure that it does not enter the specimen via surface-connected pores, since this could significantly affect the measured conductivity. The reliability of the technique has been confirmed by testing fused silica samples of known thermal conductivity. It has also been applied to sprayed zirconia and plasma electrolytic oxide (PEO) alumina coatings. The values obtained were 1.05±0.10 W m?1 K?1 and 1.63±0.35 W m?1 K?1, respectively