An ARIMA Supply Chain Model with a Generalized Ordering Policy

This dissertation develops models to understand and mitigate the bull- whip effect across supply chains. The models explain the bullwhip effect that is caused by using the up to target ordering policy in standard Material Requirement Planning (MRP) systems. In the up to target ordering policy, the orders are directly driven by actual demand oscillations. We develop the models in AutoRegressive Integrated Moving Average (ARIMA) forms for a single demand item in a tandem line supply chain model. Different from supply chain models in current literature that are based on the assumption of the up to target ordering policy with some specific ARIMA models and specific numbers of stages in supply chain, the up to target ordering policy models in this dissertation can be applied to any ARIMA demand, any or- dering lead time, and any number of stages in supply chains to derive the closed form expressions of the variation in inventory and the variation in orders. In addition, we propose the generalized ordering policy in which the up to target ordering policy is a special case. The generalized ordering policy permits manufacturers to smooth orders with the guaranteed stationary inventory in which smoothing orders is regarded as an effective way to mitigate the bullwhip effect. With the generalized ordering policy, manufacturers can control the tradeoffs between the variation in inventory and the variation in differencing orders which is stationary due to differencing. The generalized order models can be applied to any ARIMA demand, any ordering lead time, and any smoothing period. Two special cases of the generalized ordering policy are also illustrated. One is the previously mentioned up to target ordering policy that minimizes the variation in inventory. Another is the smoothing ordering policy that minimizes the variation in differencing orders. We also provide generic formulas to determine the opti- mal smoothing weights in the smoothing ordering policy for ARIMA(p; 0; q) and ARIMA(p; 1; q) orders. Finally, this dissertation introduces the bounded MRP following the rate based planning concept. We propose a simulation based technique to set the bounds into standard MRP systems for exponential smoothing or ARIMA(0,1,1) demand. With this bounded MRP, we can mitigate the bullwhip effect and reduce the conflict between production planning and infeasible capacity planning

A nonlinear optimization model on the reinforcement length of a modular block wall by varying surcharge and soil strength parameters

This study proposes a nonlinear optimization approach in designing a modular block wall which is atype of the mechanical stabilized earth wall. A nonlinear optimization model is proposed based on minimizing the reinforcement length where the constraints considered are the external stability and the internal stability. Theoptimum reinforcement length can be determined based on available soil strength parameters and the maximum surcharge. This study also includes the parametric study of the reinforced soil, retained soil, and foundation soil by varying the ranges of the wall height, surcharge, and soil strength parameters in density and friction angle to see the behaviours of the aforementioned external stability and internal stability. This can be beneficial in designing thismodular block wall encountering a poor soil condition or a large amount surcharge

A nonlinear optimization model on the reinforcement length of a modular block wall by varying surcharge and soil strength parameters

This study proposes a nonlinear optimization approach in designing a modular block wall which is atype of the mechanical stabilized earth wall. A nonlinear optimization model is proposed based on minimizing the reinforcement length where the constraints considered are the external stability and the internal stability. Theoptimum reinforcement length can be determined based on available soil strength parameters and the maximum surcharge. This study also includes the parametric study of the reinforced soil, retained soil, and foundation soil by varying the ranges of the wall height, surcharge, and soil strength parameters in density and friction angle to see the behaviours of the aforementioned external stability and internal stability. This can be beneficial in designing thismodular block wall encountering a poor soil condition or a large amount surcharge

A Damage Index for Assessing Seismic-Resistant Designs of Masonry Wall Buildings Reinforced with X-Bracing Concrete Frames

In this paper, a suitable damage index is demonstrated to assess the seismic-resistant design of masonry wall buildings reinforced with double x-bracing concrete frames. As a criterion indicative of the damage level that might occur after an earthquake, the damage index can be calculated by using analytic results, by using the Park–Ang formula on masonry wall buildings reinforced with concrete structures, and by adjusting the index values in accordance with the results of the analysed models. The data used in this study are collected from the results of four-storey concrete structures with masonry walls under cyclical lateral forces. To simulate the masonry walls’ structural behaviours for damage assessment, x-bracings placed as crosses on each bracing are used to support the compressive strength. Then, the analysis results are used to assess the damage that occurs to the masonry wall building structure by considering deformation and energy decay; additionally, a suitable damage index is calculated for each damage level. The damage index can be considered in the seismic-resistant design of masonry walls reinforced with x-bracing concrete frames

Exploring Factors Affecting Consumer Behavioral Intentions toward Online Food Ordering in Thailand

Due to the COVID-19 epidemic, ordering food online has become very popular. This study used a structural equation model to analyze the indicators that influence the decision to order food through a food-delivery platform. The theory of planned behavior and the technology acceptance model were both used, along with a new factor, the task–technology fit (TTF) model, to study platform suitability. Data were collected using a questionnaire given to a group of 1320 consumers. The results showed that attitudes toward on-line delivery most significantly affected the behavioral intentions of the consumers, followed by subjective norms. Among attitudes, perceived ease of use was the most significant, followed by perceived usefulness and trust. The study’s results revealed that TTF had the most significant impact on perceived ease of use, followed by perceived usefulness. This means that, if a food-ordering platform is deemed appropriate, consumers will continue to use it, and business sustainability will be enhanced