A monthly monetary model with banking intermediation for the euro area

JEL Classification: C32, E41, E43, E50, G21Banking intermediation, cointegration, Loan demand, Money demand, Structural VECM

Highly Abrasion-resistant and Long-lasting Concrete

Studded tire usage in Alaska contributes to rutting damage on pavements resulting in high maintenance costs and safety issues. In this study binary, ternary, and quaternary highly-abrasion resistant concrete mix designs, using supplementary cementitious materials (SCMs), were developed. The fresh, mechanical and durability properties of these mix designs were then tested to determine an optimum highly-abrasion resistant concrete mix that could be placed in cold climates to reduce rutting damage. SCMs used included silica fume, ground granulated blast furnace slag, and type F fly ash. Tests conducted measured workability, air content, drying shrinkage, compressive strength, flexural strength, and chloride ion permeability. Resistance to freeze-thaw cycles, scaling due to deicers, and abrasion resistance were also measured. A survey and literature review on concrete pavement practices in Alaska and other cold climates was also conducted. A preliminary construction cost analysis comparing the concrete mix designs developed was also completed

ISBIS 2016: Meeting on Statistics in Business and Industry

This Book includes the abstracts of the talks presented at the 2016 International Symposium on Business and Industrial Statistics, held at Barcelona, June 8-10, 2016, hosted at the Universitat Politècnica de Catalunya - Barcelona TECH, by the Department of Statistics and Operations Research. The location of the meeting was at ETSEIB Building (Escola Tecnica Superior d'Enginyeria Industrial) at Avda Diagonal 647. The meeting organizers celebrated the continued success of ISBIS and ENBIS society, and the meeting draw together the international community of statisticians, both academics and industry professionals, who share the goal of making statistics the foundation for decision making in business and related applications. The Scientific Program Committee was constituted by: David Banks, Duke University Amílcar Oliveira, DCeT - Universidade Aberta and CEAUL Teresa A. Oliveira, DCeT - Universidade Aberta and CEAUL Nalini Ravishankar, University of Connecticut Xavier Tort Martorell, Universitat Politécnica de Catalunya, Barcelona TECH Martina Vandebroek, KU Leuven Vincenzo Esposito Vinzi, ESSEC Business Schoo

Effectiveness of Air and Biomass Heating using Waste Heat from a Gasification System

A downdraft gasifier is a type of gasification system device which is used to generate a synthetic gas (syngas) from organic carbonaceous material through an incomplete combustion process. This is achieved by reacting the material at high temperatures (>700°C), without combustion, with a controlled amount of oxygen and/or steam. Previous studies had proved that by having a lower moisture content of biomass fuel and preheating of gasifying air, it can improve the quality of the syngas produced and increase the efficiency of the gasification. During gasification, the temperature of waste heat produced at the gasifier is high and it can be used to reduce the moisture content of biomass fuel and increase the gasifying air temperature before being fed into gasification system. Therefore, the objective of the project is to evaluate the effectiveness of utilizing waste heat from a gasification system for secondary drying of the biomass fuel and for heating of the gasifying air. The heat exchanger system had been designed to capture the waste heat from the gasifier wall and exhaust pipe for biomass drying and preheating of gasifying air in the drying box. The drying box designed consists of 4 main boxes which can be assembled into one. The boxes are differentiated by its location towards heat exchanger which is located at the middle of the box. The heat exchanger in the drying box was designed to dissipate the heat from flowing hot water to inside the drying box and air tube. Due to time constrain in academic calendar, the experiment was simplified by only simulating the heat exchanging process in the drying box. The experiment was performed to see the effectiveness of the system by using 60°C hot water flowing at 3.5 LPM flow rate and 150 LPM of gasifying air flow rate. The experiment was conducted by using 55% moisture content (dry basis) of oil palm frond that had been cut into block shape. The result shown from the experiments showed that the system designed fails to reduce the biomass moisture content in the drying box. However there is some increment of temperature in gasifying air, especially when the air is heated with biomass. The compactness of biomass in the drying box forces it to act like an insulation barrier around the heat exchanger. For future study, it is recommended that the drying box is designed with large surface area for biomass drying

Study on New Sampling Plans and Optimal Integration with Proactive Maintenance in Production Systems

Sampling plans are statistical process control (SPC) tools used mainly in production processes. They are employed to control processes by monitoring the quality of produced products and alerting for necessary adjustments or maintenance. Sampling is used when an undesirable change (shift) in a process is unobservable and needs time to discover. Basically, the shift occurs when an assignable cause affects the process. Wrong setups, defective raw materials, degraded components are examples of assignable causes. The assignable cause causes a variable (or attribute) quality characteristic to shift from the desired state to an undesired state. The main concern of sampling is to observe a process shift quickly by signaling a true alarm, at which, maintenance is performed to restore the process to its normal operating conditions. While responsive maintenance is performed if a shift is detected, proactive maintenance such as age-replacement is integrated with the design of sampling. A sampling plan is designed economically or economically-statistically. An economical design does not assess the system performance, whereas the economic-statistical design includes constraints on system performance such as the average outgoing quality and the effective production rate. The objective of this dissertation is to study sampling plans by attributes. Two studies are conducted in this dissertation. In the first study, a sampling model is developed for attribute inspection in a multistage system with multiple assignable causes that could propagate downstream. In the second study, an integrated model of sampling and maintenance with maintenance at the time of the false alarm is proposed. Most of the sampling plans are designed based on the occurrence of one assignable cause. Therefore, a sampling plan that allows two assignable causes to occur is developed in the first study. A multistage serial system of two unreliable machines with one assignable cause that could occur on each machine is assumed where the joint occurrence of assignable causes propagates the process\u27s shift to a higher value. As a result, the system state at any time is described by one in-control and three out-of-control states where the evolution from a state to another depends on the competencies between shifts. A stochastic methodology to model all competing scenarios is developed. This methodology forms a base that could be used if the number of machines and/or states increase. In the second study, an integrated model of sampling and scheduled maintenance is proposed. In addition to the two opportunities for maintenance at the true alarm and scheduled maintenance, an additional opportunity for preventive maintenance at the time of a false alarm is suggested. Since a false alarm could occur at any sampling time, preventive maintenance is assumed to increase with time. The effectiveness of the proposed model is compared to the effectiveness of separate models of scheduled maintenance and sampling. Inspired by the conducted studies, different topics of sampling and maintenance are proposed for future research. Two topics are suggested for integrating sampling with selective maintenance. The third topic is an extension of the first study where more than two shifts can occur simultaneously

Monitoring process variability: a hybrid Taguchi loss and multiobjective genetic algorithm approach

The common consideration on economic model is that there is knowledge about the risk of occurrence of an assignable cause and the various cost parameters that does not always adequately describe what happens in practice. Hence, there is a need for more realistic assumptions to be incorporated. In order to reduce cost penalties for not knowing the true values of some parameters, this paper aims to develop a bi-objective model of the economic-statistical design of the S control chart to minimize the mean hourly loss cost while minimizing out-of-control average run length and maintaining reasonable in-control average run length considering Taguchi loss function. The purpose of Taguchi loss function is to reflect the economic loss associated with variation in, and deviations from, the process target or the target value of a product characteristic. In contrast to the existing modeling approaches, the proposed model and given Pareto-optimal solution sets enables the chart designer to obtain solutions that is effective even for control chart design problems in uncertain environments. A comparison study with a traditional economic design model reveals that the proposed chart presents a better approach for quality system costs and the power of control chart in detecting the assignable cause