Demand Distortion Research Articles

Demand Distortions and Capacity Allocation Policies

In this paper, we describe a study of the consequences of capacity allocation mechanisms at a large semiconductor manufacturer. We use a panel data set with 300,000 observations spanning five years of forecasting and order transactions between a supplier and customers at the supplier's manufacturing facility. Using Mixed Linear Models (MLM), we study the mutual interplay between a supplier's capacity allocation mechanism and customers' demand forecasts and orders. The results of our model suggest that the interaction causes two types of distortions: inter-temporal and cross-sectional. Temporal forecast distortions result in forecast churn (short-term volatility in forecasts), undesirable forecast smoothing (a.k.a., batching), and customers exiting the facility. Cross-sectional forecast distortion (contagion) is characterized by temporal forecast distortions spreading across individual customers' forecasts, attributable to the negative externalities imposed by commonly used capacity allocation policies. We present empirical tests for the presence and significance of these distortions in our data and note the impact of churn on buffer inventory stocks and contagion's effect on risk pooling efforts. Our findings have implications for contracting, capacity planning, and CPFR initiatives in supply chains.

Emerging distribution systems in central and Eastern Europe

PurposeThe purpose of the research is to shed light on the evolution of distribution structures and its consequent implications for supply chain management (SCM) in the context of the emerging markets of Central and Eastern Europe (CEE).Design/methodology/approachA structured literature review followed by two case studies, which combine qualitative and quantitative analysis. Mainly in‐depth interviews were used, with company sales data analysis in terms of variation and forecast accuracy.FindingsIt was found that CEE distribution structures are overlapping, and along complex traditional structures there exists a possibility for a more direct approach. This modern key‐account approach improves supply chain performance, mainly due to echelon elimination and information sharing. The case studies also illustrate that supply chain demand distortion originating practices create uncertainty in demand, even in the case of modern key accounts. The findings therefore suggest that general SCM approaches of the “West” are evident and appropriate also in the “East”.Research limitations/implicationsOwing to the limited number of case studies, this research is considered exploratory. The presented two case studies are essentially illustrative examples of the distribution operations of two international companies in CEE markets.Practical implicationsFor practitioners, the two case studies provide important insight on the nature of alternative distribution structures in CEE, and what the level of forecast accuracy and the demand fluctuation may be expected. It is proposed that the emerging opportunities for supply chain partnership development should be carefully reviewed.Originality/valueThe paper draws upon real‐life data from emerging CEE markets with an approach that is not commonly used in distribution and SCM studies on CEE.

An ant direction hybrid differential evolution heuristic for the large-scale passive harmonic filters planning problem

This article presents a heuristic which combines the orthogonal array experiment technique and an ant direction hybrid differential evolution algorithm (ADHDEOA) for planning of a large-scale passive harmonic filters problem. The addressed problem has a multi-bus and under abundant harmonic current sources in the system. In this study, an orthogonal array is first conducted to obtain the initial solution. Next, an ant direction hybrid differential evolution (ADHDE) is applied to search for a near optimum solution. The objective is to minimize the cost of the filter, the total demand distortion of harmonic currents and the total harmonic distortion of voltages at each bus simultaneously. In order to determine a set of weights of each term in the objective function, the simplest and most efficient form of triangular membership functions has been considered. The designed heuristic ADHDEOA is applied to a practical harmonic problem in a steel plant, and three design schemes are compared to demonstrate the performance of the ADHDEOA.

Optimal Design of Discrete-Value Passive Harmonic Filters Using Sequential Neural-Network Approximation and Orthogonal Array

This paper presents a method for combining sequential neural-network approximation and orthogonal arrays (SNAOA) in the planning of large-scale passive harmonic filters. An orthogonal array is first conducted to obtain the initial solution set. The set is then treated as the initial training sample. Next, a back-propagation sequential neural network is trained to simulate the feasible domain for seeking the optimal filter design. The size of the training sample is greatly reduced due to the use of the orthogonal array. In addition, a restart strategy is also incorporated into the SNAOA so that the searching process may have a better opportunity to reach a near global optimum. To illustrate the performance of the SNAOA, a practical harmonic mitigation problem in a chemical plant is studied. The results show that the SNAOA performs better than the original scheme and satisfies the harmonic limitations with respect to the objective of minimizing the total demand distortion of harmonic currents and total harmonic distortion of voltages. Filter loss, reactive power compensation, and the constraints of individual harmonics are also considered. Additional results related to SNAOA are also reported and discussed as well.

Collateral restrictions and liquidity under-supply: a simple model

We show that very little is needed to create liquidity under-supply in equilibrium. Credit constraints on demand by themselves can cause an under-supply of liquidity, without the uncertainty, intermediation, asymmetric information or complicated international financial framework used in other models in the literature. We show that the under-supply is a non-monotone function of the demand distortion that causes it, a result that may have interesting implications for emerging markets economies. Finally, when we make the credit constraint endogenous, the inefficiency can be large due to the presence of a multiplier.

Melbourne Pathology

Melbourne Pathology, a subsidiary of Sonic Health Care, provided a comprehensive range of pathology services as an aid in the diagnosis and treatment of patients in Melbourne and Central Victoria. In a capped funding and highly regulated market such as the pathology service market in Australia, the only way in which the sales of a provider could grow was usually at the expense of another provider. To combat this situation, Melbourne Pathology opted to compete by providing higher quality service and faster turnaround time. The recent results of Melbourne Pathology, however, indicated that although the average turnaround time was within the promised targets, significant percentage of jobs in routine category and over 10% of jobs in the urgent category failed to meet the established targets. The case is primarily intended to illustrate the impact of demand distortions in a service setting that arise due to lack of coordination among various entities in the service value chain and a failure to have an integrated perspective that aligns all departments towards a common goal. This phenomenon is similar to the bullwhip effect in supply chains of manufactured products which has received considerable attention during the past decade. The case provides opportunities for students to develop corrective actions to mitigate this problem.

An Improved Control Algorithm for Active Filters

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> This paper proposes a new control algorithm resulting in significant advantages toward smooth control of an active filter (AF). The majority of existing feedforward control methods of the AF system result in switching notches (sharp-rising ripples) in the supply current during transitions of stepped waveshaped nonlinear load current. This is due to switching signals for the AF devices, which are obtained by comparison of the sensed and reference currents of the AF. The proposed control algorithm is based on feedback control, wherein, switching signals for the AF devices are obtained by comparing sensed and reference supply currents. This not only eliminates switching notches in the supply currents but also reduces the supply current total demand distortion below the 5% mark recommended by the IEEE-519 standard. A TMS320C31 digital signal processor is used for real-time implementation of the proposed algorithm. To establish its viability and flexibility, the proposed algorithm is also experimented with a laboratory prototype of the AF system made of a reduced number of switches. </para>

Optimization of a passive harmonic filter based on the neural-genetic algorithm with fuzzy logic for a steel manufacturing plant

This report presents a method which combines an artificial neural network and a genetic algorithm (ANNGA) in the planning of large-scale passive harmonic filters (PHF) for a multi-bus system under abundant harmonic current sources. The objective is to minimize the cost of the filter, its power loss, the total demand distortion of harmonic currents and the total harmonic distortion of voltages at each bus, simultaneously. First, a Taguchi experiment was used to perform an efficient experimental design and analyze the robustness of the PHF. Following, the results from the Taguchi experiment were used as the learning data for an artificial neural network (ANN) model that could predict the parameters at discrete levels. Finally, a genetic algorithm was applied to obtain a robust PHF setting of the parameters with continuous variables. Besides, to deal with the multiple objectives of the addressed problem, the membership function from fuzzy logic theory is also adopted in the algorithm for determining the weight of each single objective considered. A search for an optimal solution was applied to the harmonic problems in a steel plant. The results showed that the performance of the harmonic filters was significantly improved when compared with the original design.

The Welfare Effects of Inflation: A Cost-Benefit Perspective

This paper reviews theory and evidence of the welfare effects of inflation from a costbenefit perspective. Basic models and selected empirical results are discussed. Historically, in assessing the welfare effects of inflation, the distortion of money demand played a prominent role. More recently, interactions of inflation and taxation came into focus. Growth effects of inflation as well as welfare effects of unanticipated inflation and of inflation uncertainty are also addressed. To assess the policy question whether inflation should be reduced or eliminated, the costs of disinflation play a role. Finally, the trade-off between the benefits of reducing inflation and the costs of disinflation is discussed and an overall assessment of the net welfare effects of achieving price stability is provided.

Harmonic Reducing ANN Controller for a SVC Compensating Unbalanced Fluctuating Loads

This paper presents the development of an artificial neural network (ANN) controller for a Static Var Compensator (SVC) system compensating unbalanced fluctuating loads. The proposed controller can balance and reduce the reactive power drawn from the source under unbalanced loads while keeping harmonic injection to the system due to SVC operation low. The first stage of controller development is a fuzzy logic based control algorithm. This algorithm determines a number of possible operating states of SVC for a given load condition and calculates corresponding harmonics injections. Then a fuzzy logic system is used to rank those operating states in terms of the magnitude of the reactive power drawn from the source and the harmonic injection level indicated by Total Demand Distortion (TDD). The best operating state is selected based on the ranking score assigned by the fuzzy logic ranking system. Finally, computational speed of the controller is improved by replacing the analytical and fuzzy computations by a set of neural networks trained with data generated with fuzzy logic based controller.

인천 국제공항청사 경전철 도입에 따른 고조파 영향 분석

최근 전기철도에 고속화 기술이 적용되고 열차 구동장치 및 제어계통에 전력용 반도체 소자가 사용되고 있으며, 전기철도 구동시스템의 주요 구성장치인 인버터와 컨버터의 동작을 제어하는 전력전자 소자의 이용은 고조파를 발생의 원인이 된다. 이러한 고조파는 통신장해 및 전류, 전압의 전력품질 저하 등 여러 가지 문제를 발생시킨다. 따라서 본 논문에서는 인천 국제공항에 설치되고 있는 경전철 전력설계의 전력시스템 평가 및 개발을 통해 상위 계통에 미치는 영향 및 전력시스템에서 발생할 수 있는 장애 요인을 사전에 예측 계산하여 이에 대한 대책을 마련하여 전력품질 향상에 목적이 있다. 인천 국제공항청사 내의 전력시스템의 전력품질 문제 접근에 있어 경전철이 운행될 경우 발생할 수 있는 여러 문제 중 특히 전압강하 및 전압불평형에 영향을 미치는 고조파 발생에 대해 분석하였다. 고조파 분석은 IEEE 519-1992(IEEE 141-1993과 동일) 기준에 의거하여 행하였다. 또한 인천 공항청사의 운행되는 경전철은 동적 전력시스템 해석 프로그램인 PSCAD/EMTDC 모델링하고 이의 시뮬레이션 결과를 이용하여 고조파 분석을 하였다.

Supply Chain Dynamics, a Case Study on the Structural Causes of the Bullwhip Effect

This is a case study about the mod el ling of a sup ply chain de ci sion struc ture of a Mex i can bot tling com pany. We find that by mod el ling the in for ma tion and de ci sion struc ture of sup ply chains, it is pos si ble to iden tify man a ge rial pol i cies and in for ma tion flows that dis tort and am plify mar ket de mand sig nals. In the sec ond part of the pa per we use two sce nar ios to ana lyse var i ous changes in pol i cies. This pa per il lus trate not only an in no va tive form to study the Bull whip Ef fect nor only a dif fer ent way to model sup ply chains us ing Sys tem Dy nam ics, but also it es tab lishes a re la tion ship be tween in for ma tion struc tures, de ci sions rules, and de mand dis tor tion in sup ply chains.

Harmonics impacts evaluation for single-phase traction load

A planned electric utility substation supplying the single-phase traction load at New Haven, CT, USA was evaluated with regard to several important aspects of power quality. Harmonics: the trains are non-linear and time-varying loads. Harmonic current levels were measured at a nearby single-phase traction substation, which serves the same line as the future New Haven substation. These results show that the third harmonic current and the total demand distortion (TDD) exceed the limits recommended in IEEE Standard 519-1992, IEEE (1993), hereafter referred to as IEEE 519. Voltage unbalance: the traction load is supplied by two 15-MVA single-phase transformers, each connected across phases A–C of the 115-kV line. Measurement results at a nearby 115-kV substation indicate a voltage unbalance of less than 1%, which is well within acceptable limits. Calculations for the New Haven substation location similarly show a voltage unbalance of less than 1%, with a 15-MVA load. Voltage fluctuations: the variable traction load can introduce flicker, a voltage fluctuation, which produces annoying visual changes in the intensity of electric lights. The measurement results at the nearby 115-kV substation show both the short-term (Pst) and long-term (Plt) flicker indicators are well below the recommended limits of 1.0 and 0.8, respectively.

Evidence of bullwhip effect in healthcare sector: causes, consequences and cures

The primary issue explored in this research is how demand distortions, called the 'bullwhip' effect, create inefficiencies for firms in the service industries. Much of the prior research has focused on documenting the existence of bullwhip effect in a number of manufacturing situations and more recently, authors have posited possible causes and cures for this phenomenon. To our knowledge, there has not been any published research that has investigated the existence of bullwhip effect in service settings. In this paper, we demonstrate the existence of bullwhip effect in the healthcare sector through case studies. We also discuss the possible effects and propose corrective actions.

Application of combined feasible-direction method and genetic algorithm to optimal planning of harmonic filters considering uncertainty conditions

The paper presents an approach of combining a feasible-direction method and a genetic algorithm (FDM+GA) to investigate the planning of large-scale passive harmonic filters. The optimal filter scheme can be obtained for a system under abundant harmonic-current sources where harmonic-amplification problems should be avoided. The design is to minimise the total demand distortion of harmonic currents and total harmonic distortion of load bus voltages. Filter loss, reactive-power compensation and constraints of individual harmonics can be considered in the design procedures. The constraints of harmonics with orders lower than the filter tuned points have been set stricter to avoid amplification of noncharacteristic harmonics. The search for the global optimal solution is applied to the harmonic problems in a steel plant, where both AC and DC are furnaces are used and a static Var compensator (SVC) is installed. Three design schemes are compared to demonstrate the performance of the proposed method. Finally, expectations and standard deviations of objective functions are used to present effects of filter-parameter detuning, loading uncertainty and changes of system impedance.

Optimal multiobjective planning of large-scale passive harmonic filters using hybrid differential evolution method considering parameter and loading uncertainty

This paper is used to investigate the optimal multiobjective planning of large-scale passive harmonic filters for a multibus system under abundant harmonic current sources using the hybrid differential evolution (HDE) method. The migrant and accelerating operations embedded in HDE are used to overcome traps of local optimal solutions and problems of time consumption. The design purposes are to minimize the total demand distortion of harmonic currents and total harmonic distortion of voltages at each bus. Filters loss, fundamental reactive power compensation, and constraints of individual harmonics are also considered. The search for the global optimal solution is applied to the harmonic problems in a steel plant, where both ac and dc arc furnaces are used and a static var compensator is installed. Three design schemes are compared to demonstrate the performance of HDE. Finally, expectations of objective function are used to present the effects of filter parameter detuning and furnace loading uncertainty.

Expectation Traps in a New Keynesian Open Economy Model

This paper illustrates that the introduction of a money demand distortion into an otherwise standard New Keynesian Open Economy model generates multiple discretionary equilibria. These equilibria arise in the form of expectations traps whereby the monetary authority is trapped into validating expectations of the private sector because failing to do so is costly. One implication of the model is that provided initial inflation expectations are sufficiently anchored the global Friedman rule emerges as an equilibrium under discretion. It is therefore a time-consistent outcome and hence fully sustainable even in absence of a commitment device or reputational considerations.

Simulating Effects of Supply Chain Configuration on Industrial Dynamics in the Forest Sector

Two wood games are developed based on the structure and dynamics of the Beer Game. By introducing divergent and convergent flows in the supply chain, the relevance to the forest sector is increased. Using eight players in each run, the game is, in essence, a simulation tool that includes the human aspect in decision-making. The wood game is used to simulate the challenges that may be met when introducing a greater degree of customer orientation in the forest sector. Performance is measured using total system costs, amplification of demand variation and basic statistics of order rates. Results from pilot experiments indicate that performance and predictability of the system are negatively affected by increasing the complexity of the supply chain. The level of demand distortion varies considerably between different games. Distorted demand signals may complicate the planning and execution of upstream operations.

Persistency and Money Demand Distortions in a Stochastic DGE Model with Sticky Prices

Recently macroeconomists have intensified their efforts to develop models that are able to generate persistent reactions of real variables to monetary shocks in stochastic DGE models with nominal rigidities. This has proven to be quite difficult in models with price staggering only. Most papers show that output is above steady state only as long as prices are fixed for the firms. In this article particular attention is given to the role of money demand and to the form of the utility function. I consider cash-in-advance- (CIA) as well as money-in-theutility-function- (MIU) models, with CRRA and GHH preferences, to evaluate their ability to generate persistence. Persistent reactions emerge only with a high value of the elasticity of labor supply with respect to the real wage and an interest rate sensitive money demand function. CIA-models generally create more persistence than MIUmodels. In the CIA-setup a CRRA utility function generates more persistence than GHH preferences. The results highlight the importance of the way money is introduced in a New Neoclassical Synthesis

Supply chain simulation – a tool for education, enhancement and endeavour

This paper describes how a participative simulation model is used to demonstrate supply chain dynamics and to model possible improvements to an entire supply chain. A three-year research project in the automotive steel supply chain found that lack of understanding of the core processes throughout the supply chain caused distortion and amplification of both demand and supply patterns. In consequence, this deficit of information is often replaced with inventory — resulting in increased lead times and pipeline cost. At the start of the project there was relatively little collaboration in the supply network. The ‘Lean Leap Logistics Game’ was developed primarily to foster collaboration. To achieve this, the game had to model reality, and was built on a series of mapping activities. Unexpectedly, it turned out that developing and running the game led to insights into scheduler behaviour, scheduling decision making, prioritising improvement activities and into supply chain dynamics, especially the ‘Forrester’ or ‘Bullwhip’ effect. By presenting the experiences of using supply chain simulations, this paper aims at encouraging both academics and practitioners to use this tool to demonstrate and discuss supply chain improvements by simulating their individual characteristics in order to deploy holistic improvements, rather than partial or ‘island’ solutions.