猪鸡常用饲料成分及营养价值变异性初探

使用Foxpro(2.5b),建立了猪鸡常用饲料成分及营养价值动态数据库管理系统。在此基础上对饲料成分及营养价值的变异性进行了初步研究。任何饲料成分及营养价值均具有变异性,但线性规划配方算法中没有考虑这种变异性。本文计算出了四川猪(31种原料)、鸡(19种饲料原料)常用饲料成分及营养价值的平均值、标准差及变异系数,作为该系统移植到饲料厂前的系统基底数据。     

Improving the fatigue life of a vehicle knuckle with a reliability-based design optimization approach

A major issue in vehicle industry is the presence of variability in the physical properties and manufacturing processes. Deterministic approaches are unable to take into account these variabilities without leading to oversized structures. The necessity of assessing the robustness of a particular design requires a new methodology based on reliability analysis and design optimization through probabilistic models of design variables.     

Evaluation of Lag Schedules and Rules on Persistent Response Variability With Preschoolers in a Group

In the present study, experimenters evaluated the influence of lag schedules of reinforcement in combination with accurate and inaccurate (complete and incomplete) rules on the response variability of naming category items for typically developing preschoolers in a group format. Results showed that when lag schedules were introduced with 2 categories, response variability generalized to the third category. Furthermore, after participants experienced the lag schedule, variability persisted when the contingency no longer required variability. Participants continued to vary their responses unless the rule and contingency required them to repeat responses. We discuss potential clinical applications of using lag schedules in a group format and including rules during teaching, as well as directions for future research in this area.     

A variability taxonomy to support automation decision-making for manufacturing processes

Abstract

Although many manual operations have been replaced by automation in the manufacturing domain in various industries, skilled operators still carry out critical manual tasks such as final assembly. The business case for automation in these areas is difficult to justify due to increased complexity and costs arising out of process variabilities associated with those tasks. The lack of understanding of process variability in automation design means that industrial automation often does not realize the full benefits at the first attempt, resulting in the need to spend additional resource and time, to fully realize the potential. This article describes a taxonomy of variability when considering the automation of manufacturing processes. Three industrial case studies were analyzed to develop the proposed taxonomy. The results obtained from the taxonomy are discussed with a further case study to demonstrate its value in supporting automation decision-making.     

Recursive Behavior of Safety Stock Reduction: The Effect of Lead‐Time Uncertainty

Motivated by a recent paper on the effect of lead‐time variability reduction on safety stocks, we provide evidence of the recursive nature of safety stock changes. When lead times follow a gamma distribution we demonstrate that, for cycle service levels between .60 and .70, the reduction of lead‐time variability will first increase safety stock and then either recursively decrease safety stock or make it remain constant. We also numerically show the existence of the recursive effect. A two‐by‐two matrix is introduced to assist managers in making decisions regarding safety stock policy.     

Mean residual life ordering

A new partial ordering among life distributions in terms of their mean residual life is introduced. This ordering is weaker than the hazard rate ordering but it is stronger than the variability ordering. Characterizations of the DMRL and NBUE distribution are given.     

Coping with Group Behaviors in Uncertain Quality Function Deployment

Quality function deployment (QFD) is a planning and problem‐solving tool gaining wide acceptance for translating customer needs (CNs) into technical attributes (TAs) of a product. It is a crucial step to derive the prioritization of TAs from CNs in QFD. However, it is not so straightforward to prioritize TAs due to two types of uncertainties: human subjective perception and user variability. The main focus of this article is to propose a group decision‐making approach to uncertain QFD with an application to a flexible manufacturing system design. The proposed approach performs computations solely based on the order‐based semantics of linguistic labels to eliminate the burden of quantifying qualitative concepts in QFD. Moreover, it incorporates the importance weights of users and the concept of fuzzy majority into aggregations of individual fuzzy preference relations of different TAs in order to model the group behaviors in QFD. Finally, based on a quantifier‐guided net flow score procedure, the proposed approach derives a priority ranking with a classification of TAs into important and unimportant ones so as to provide a better decision‐support to the decision‐maker. Due to the easiness in articulating preferential information, our approach can reduce the cognitive burden of QFD planning team and give a practical convenience in the process of QFD planning.     

Influence Functions for the Coefficient of Variation,Its Inverse,and CV Comparisons

Expressions are found for the influence function of the coefficient of variation, CV, and its reciprocal, the signal to noise ratio. These functions are free of units, which permits the comparison of the values of the CVs of continuous positive distributions to a perturbation by a small amount of probability at x. For a CV ≤0.5, the influence function response will be negative, of modest size, for values of x near E(X). For such values of a CV and of x, the influence function for 1/CV will be positive and its values will be substantial. These results imply similar behavior by the sample coefficient of variation or its reciprocal, which is supported by simulation studies in the literature. Values of the CV ≥1 are associated with large negative responses of their influence functions. The distributions producing such responses often have densities that decrease from positive infinite to zero on the positive axis with a long tail to the right. An influence function for the difference of two coefficients of variation is also obtained.     

Measures of Variability for Model-Based Seasonal Adjustment Procedures

An algorithm is derived that develops measures of variability for the estimates of the nonseasonal component computed from a model-based seasonal adjustment procedure. The measures of variability are developed from signal extraction theory. Properties of components of the variance are developed, and the behavior of the variance is investigated for one popular time series model. The results are illustrated by using real data.