A conceptual hybrid framework for industrial process improvement: integrating Taguchi methods,Shainin System and Six Sigma

Design of Experiments (DoE) has evolved as powerful industrial statistics tool for managing and improving processes in diverse industries. The three broad approaches of DoE in practice: classical or traditional methods, Taguchi methods and Shainin System (SS), have their merits and demerits for a extensive industrial experimentation. Nonetheless, the power of these DoE approach is not fully harnessed in established process improvement frameworks in industries. On the other side, Six Sigma DMAIC is a well-accepted methodology for improving process capability through focus on customer’s requirement (CTQ). The use of DoE in traditional DMAIC framework is limited to quantification of influence factors on CTQ. To offer a contribution to this paucity, this paper proposed a conceptual Six Sigma/DOE hybrid framework aiming to integrate SS, Taguchi methods and Six Sigma DMAIC for process improvement in complex industry environment. A case on improving DF generation process in shock absorber assembly was developed to validate the effectiveness of the framework for intricate problem-solving.     

Using Shainin DOE for Six Sigma: an Indian case study

Shainin design of experiments (DOE) offers a powerful and effective experimental design approach for solving the chronic quality problems that plague manufacturers worldwide. However, the academic literature still contains a few empirical studies on the use of non-statistical Shainin DOE tools to simplify the quality improvement initiatives. In order to overcome this deficiency, this case describes framework for incorporating Shainin experimental design within Six Sigma define–measure–analyse–improve–control and tests its effectiveness in an Indian automotive gear manufacturing unit. Shainin tools such as Paired Comparison, Product/Process search, Concentration chart, B vs. C analysis, Pre-control chart were employed to analyse, improve and control the gear manufacturing process. The study provides stimulus for the wider application of Shainin experimental design approach for industrial experimentation.     

HYBRID R&D

We develop a model of R&D collaboration in which individual firms carry out in‐house research on core activities and undertake bilateral joint projects on non‐core activities with other firms. We develop conditions on the profit functions of the firm under which R&D investments in different projects of a firm are complementary. We show that this condition is met by standard price and quantity setting oligopoly models. We then study the relation between the number of joint projects and investments and profits. In this context, we identify a second aspect of complementarity: Equilibrium investments in in‐house as well as in each joint project are increasing in the number of projects. However, we find that an increase in number of joint projects of all firms lowers collective profits, suggesting the presence of excessive incentives for conducting research. (JEL: L13, L14, L22, O31, O32)     

Three-stage and ‘accelerated’ sequential procedures for the mean of a normal population with known coefficient of variation

Three-stage and ‘accelerated’ sequential procedures are developed for estimating the mean of a normal population when the population coefficient of variation (CV) is known. In spite of the usual estimator, i.e. the sample mean, Searls' (1964 Searls, DT. (1964). The utilization of a known coefficient of variation in the estimation procedure. J. Amer. Statist. Assoc, 50: 1225–1226.  ) estimator is utilized for the estimation purpose. It is established that Searls' estimator dominates the sample mean under the two sampling schemes.     

Large deviation local limit theorems for ratio statistics

Let {T_n, n ≥ 1} be an arbitrary sequence of nonlattice random variables and let {S_n, n ≥ 1} be another sequence of positive random variables. Assume that the sequences are independent. In this paper we obtain asymptotic expression for the density function of the ratio statistic R_n = T_n/S_n based on simple conditions on the moment generating functions of T_n and S_n. When S_n = re, our main result reduces to that of Chaganty and Sethura-man[Ann. Probab. 13(1985):97-114]. We also obtain analogous results when T_n and S_n are both lattice random variables. We call our theorems large deviation local limit theorems for R_n, since the conditions of our theorems imply that R_n → c in probability for some constant c. We present some examples to illustrate our theorems.     

Surveying and producing the frontier in nineteenth century Manipur: challenges and practices

ABSTRACT

The second half of the nineteenth century was a turning point in the history of modern Manipur when it collaborated with the British in the first Anglo-Burmese War of 1824. With the conclusion of the treaty of Yandaboo 1826, Manipur was transformed into a frontier zone. In this backdrop, the paper explores the pre-colonial notion of territory and how it competed with the European notions of space. Boundaries were fluid, and land was perceived more in terms of people and social relations. The paper also highlights the impact of state formation and territorialisation on identity formation by referring to the changes in the management of the hills and the valley after the 1891 Anglo-Manipuri War. Demarcation of land and boundaries submitted to the logic of rule and control which resulted in the classification of land and people into far more rigid categories like the separate management of the hills and the valley.     

An alternative method for forecasting price volatility by combining models

In this article, we study the volatility in the monthly price series of edible oils in domestic and international markets using the two popular family of nonlinear time-series models, viz, Generalized autoregressive conditional heteroscedastic (GARCH) models and Stochastic volatility (SV) models. To improve the forecasts of the volatility process, we also propose a new method of combining the volatility of these two competing models using the powerful technique of Kalman filter. The individual models as well as the combined models are assessed on their ability to predict the correct directional change (CDC) in future values as well as other goodness-of-fit statistics. Further, forecasting performance are also evaluated by computing various measures to validate the proposed methodology.     

Exploring the influence of pre-training factors on training effectiveness-moderating role of trainees’ reaction: a study in the public sector in India

Organizations invest in training initiative with an objective to improve the performance of its employees and ultimately organizational performance. However, training literature highlights the gap between the learning and the transfer of learning at the workplace. Thus, there is a need to have a deeper understanding of those variables which contributes to training transfer/effectiveness. This study is an attempt to understand those organizational factors that can help in improving training effectiveness. Data was collected at three different points of time (before training, immediately at the end of training and after some time of training) to determine the antecedents of motivation to learn and the training effectiveness. Findings of the study reveal that motivation to learn mediates the relationship between the predictor variables – training needs analysis, training information and type of training, and the resultant variable training effectiveness. Also, trainees’ reaction towards training was found to moderate the relationship between trainees’ motivation to learn and training effectiveness. The study reinforces the significance of organizational factors in ensuring motivation to learn and training effectiveness. Theoretical and managerial implications are discussed in the paper.     

Matching and Network Effects

The matching of individuals in teams is a key element in the functioning of an economy. The network of social ties can potentially transmit important information on abilities and reputations and also help mitigate matching frictions by facilitating interactions among “screened” individuals. We conjecture that the probability of two individuals forming a team falls in the distance between the two individuals in the network of existing social ties. The objective of this paper is to empirically test this conjecture. We examine the formation of coauthor relations among economists over a twenty‐year period. Our principal finding is that a new collaboration emerges faster among two researchers if they are “closer” in the existing coauthor network among economists. This proximity effect on collaboration is strong: Being at a network distance of 2 instead of 3, for instance, raises the probability of initiating a collaboration by 27%. (JEL: C78, D83, D85)     

Generating random points in a ball

A fast method is presented for generating pseudorandom uniform points in a ball of dimension 3, 4, or 5.