Fluctuations In Market Demand Research Articles

The Usefulness of Capacity Cost Reports in Increasing Profit Performance: An Experimental Study

One of the recent innovations in modern managerial accounting is the practice of reporting unused capacity costs. This experimental study is conducted using a 2x2x2x2x12 mixed-subjects design aiming to answer: (1) whether reporting unused capacity cost is benefiting to decision maker, that will reduce unused capacity; (2) whether, by considering market demand fluctuation in long-term periods, decision makers who receive capacity cost reports will outperform the other decision makers who did not receive capacity cost reports; (3) whether a linear model could be used to reduce negative impact (decreasing profit) that is suggested to be caused by capacity cost reports; and (4) whether locus of control interacts with capacity cost report to influence companies’ profit performance. One hundred and fifty eight undergraduate students of FEUKWMS participated in this experiment after they were deemed to have passed the manipulation checks and answered the research questions in full. There are several findings: first, by considering the within-subject period, this experiment supports a previous study (Buchheit, 2003), which found significant influence from interaction of variable Period*Cap_Rep*Demand to capacity decision (F-value 2.5806, p-value <0.05); second, 12 periods of within-subject couldn’t prove the anchoring-and-adjustment bias which causes non-optimally capacity cost reports benefit; third, there is an emerging indication about the influence of linear model and/or locus of control on a company’s performance, although it isn’t statistically significant. This provides evidence that implementing modern management accounting innovations needs objective mathematical/statistical tools and/or subjective consideration that arise from decision makers’ locus of control.

Product Lifecycle Oriented Quality Design System into Supply Chain

To cope with the challenges of conventional quality design system applied in supply chain, a new method of product lifecycle oriented quality design mode, which integrates voice of customer, quality function deployment (QFD) and failure modes and effect analysis (FMEA), and corresponding organization and function model were all put forward. This mode dealt mainly with constructing and running product lifecycle oriented quality design system, integrated several key technologies such as the integration of QFD and FMEA, task distribution of quality design, integrated technology of computer-supported-collaborative work (CSCW). On the basis of these, applying Java, JSP and JavaServlet to the system, improve working efficiency and shorten the development cycle so as to respond to the fluctuation of market demands as quick as possible. The quality design of some automobile was introduced as an example to verify that the system developed would efficiently meet the requirements of supply chain.

Research about Short- Term Production Capacity Decision-Making

Under the circumstances of uncertain fluctuation of market demand, the degree of matching between production capacity and customers demand can affect the cost, the efficiency and the profits of an enterprise. Choosing the appropriate production capacity level is an important task for decision makers. The paper analyzes the characters of the short-term demand variation, the matching between the capacity and the demand, and its influence on the enterprise. Supposing the short-term demand varies seasonally, and the objective is minimum the loss of mismatch between the production capacity and market demand.Then,short-term production capacity decision model has been developed.Based on the model, this paper has probed into the mismatching loss of three strategies: fixed capacity strategy, subsection adjustment capacity strategy and dynamic adjustment capacity strategy,and an optimal capacity strategy is provided. By fixing the capacity-demand mismatching loss and changing the capacity adjustment rate, this paper also studies the sensitivity of the capacity strategy. The result shows that, firstly, as the capacity adjustment rate is less than a certain numerical value, the dynamic adjustment capacity is the optimal choice; secondly, as the capacity adjustment rate exceeds a certain numerical value, the optimal one is fixed capacity strategy; finally, as the rate falls in some specific area, the optimal one is subsection adjustment capacity strategy. One practical example is provided to prove the model's validity.

Data driven production modeling and simulation of complex automobile general assembly plant

Flexible manufacturing and customization has long been a topic in modern manufacturing society. However, challenges still remain on the responsiveness of production system to the fluctuation of market demand. In this paper, we developed a data driven simulation methodology to automatically model a production system and rapidly modify the model corresponding to dynamic requirements and real time information. This methodology provides a “rapid prototyping” capability for production system modeling and enables a quick analyzing and remodeling capability to respond to the fluctuation of demands. The approach is developed and applied to an automotive general assembly plant with an online material handling system. A complete information model based on IDEF1X is constructed for this domain specific modeling and simulation. The main simulation modules for assembly line and material handling system of the plant floor are analyzed and a simulator is implemented in ARENA by SIMAN/VBA program. The case study of an automotive assembly plant shows that the data driven approach enables the modeling and simulation of the complex assembly plant in a “real-time” fashion and therefore effectively improve the responsiveness and flexibility of the production line.

Production planning and performance optimization of reconfigurable manufacturing systems using genetic algorithm

To stay competitive in the new dynamic market having large fluctuations in product demand, manufacturing companies must use systems that not only produce their goods with high productivity but also allow for rapid response to market changes. Reconfigurable manufacturing system (RMS) is a new paradigm that enables manufacturing systems to respond quickly and cost effectively to market demand. In other words, RMS is a system designed from the outset, for rapid changes in both hardware and software components, in order to quickly adjust its production capacity to fluctuations in market demand and adapt its functionality to new products. The effectiveness of an RMS depends on implementing its key characteristics and capabilities in the design as well as utilization stage. This paper focuses on the utilization stage of an RMS and introduces a methodology to effectively adjust scalable production capacities and the system functionalities to market demands. It is supposed that arrival orders of product families follow the Poisson distribution. The orders are lost if they are not met immediately. Considering these assumptions, a mixed integer nonlinear programming model is developed to determine optimum sequence of production tasks, corresponding configurations, and batch sizes. A genetic algorithm-based procedure is used to solve the model. The model is also applied to make decision on how to improve the performance of an RMS. Since there is no practical RMS, a numerical example is used to validate the results of the proposed model and its solution procedure.

A New Method of Quality Control for New Product Development

To cope with the challenges of product quality design system applied in new product development (NPD), a new method of quality control for NPD-collaborative quality design mode, which integrates voice of customer, quality function deployment (QFD) and failure modes and effect analysis (FMEA) , and corresponding functional modules and framework were all put forward. This mode dealt mainly with constructing and running collaborative quality design system, integrated several enabling technologies such as the integration of QFD and FMEA, task distribution of quality design, integrated technology of computer-supported-collaborative work (CSCW). On the basis of these, applying Java, JSP and JavaServlet to the system, improve working efficiency and shorten the development cycle so as to respond to the fluctuation of market demands as quick as possible. The quality design of some automobile was introduced as an example to verify that the system developed would efficiently meet the requirements of NPD.

A Method of Quality Control for Networked Collaborative Product Development

To cope with the challenges of product quality design system applied in networked collaborative product development (NCPD), a new method of quality control for NCPD-collaborative quality design mode, which integrates voice of customer, quality function deployment (QFD) and failure modes and effect analysis (FMEA) , and corresponding functional modules and framework were all put forward. This mode dealt mainly with constructing and running collaborative quality design system, integrated several enabling technologies such as the integration of QFD and FMEA, task distribution of quality design, integrated technology of computer-supported-collaborative work (CSCW). On the basis of these, applying Java, JSP and JavaServlet to the system, improve working efficiency and shorten the development cycle so as to respond to the fluctuation of market demands as quick as possible. The quality design of some automobile was introduced as an example to verify that the system developed would efficiently meet the requirements of NCPD.

Design of part family robust-to-production plan variations based on quantitative manufacturability evaluation

This paper presents a systematic method for designing part families whose production costs are insensitive to changes in production plans due to market demand fluctuations. A unified feature-based representation of functional geometry and manufacturability has been developed to manipulate and evaluate part designs. Based on this information and production plans for multiple periods, an optimization-based method provides alternative part designs. The manufacturability of the part designs is quantitatively estimated by the facility cost of the manufacturing system best configured for a given part family and the average cycle time estimated by the discrete event simulation of production scenarios. Redesign suggestions are made on datum definitions of the original parts. Two case studies of a family of prismatic parts and that of turned parts are given to demonstrate the effectiveness of the proposed method.

Production planning in fuzzy environment

This paper describes a fuzzy system designed to support production planning in an industrial unit producing cardboard boxes. In this industrial unit, orders forn boxes of widthw, lengthl, heighth, made ofq layers of typek paper for delivery int units of time are produced. In the production of such orders apart from meeting the orders specifications, it is usually tried to minimize the margin trim loss, the number of machine setups and the holding cost of the finished orders. Considering the dynamism of production systems that are influenced by such factors as market demand fluctuations, changes in commercial priorities, raw material availability and production capabilities, we solve this multi-objective problem by fuzzy set theory.