Search results

The purpose of this paper is to develop a monitoring multiple-stream processes control chart with a finite mixture of probability distributions in the manufacture industry.

Data were collected during production of a wheat-based dough in a food industry and the control charts were developed with these steps: to collect the master sample from different production batches; to verify, by graphical methods, the quantity and the characterization of the number of mixing probability distributions in the production batch; to adjust the theoretical model of probability distribution of each subpopulation in the production batch; to make a statistical model considering the mixture distribution of probability and assuming that the statistical parameters are unknown; to determine control limits; and to compare the mixture chart with traditional control chart.

A graph was developed for monitoring a multi-stream process composed by some parameters considered in its calculation with similar efficiency to the traditional control chart.

The control chart can be an efficient tool for customers that receive product batches continuously from a supplier and need to monitor statistically the critical quality parameters.

The purpose of this paper is to identify the critical success factors (CSFs) associated with the Six Sigma (SS) implementation in companies operating in Brazil.

The research was tested based on survey questionnaire responses from a sample of 45 Brazilian manufacturing and services companies that have implemented SS programmes. An exploratory factorial analysis (EFA) was conducted to statistically identify conclusions regarding CSFs in SS implementation.

Based on the survey of empirical data, the investigated individual CSFs were reduced in five main critical factor categories: data availability, prior infrastructure and training, goals and gains, implementation of the solution and resistance to change. They have been shown to be the extremely important factors for SS implementation in Brazilian companies.

This study helps SS managers focus on the most effective factors (best practices) in SS implementation. Consequently, this may guide a company’s resources allocation and efforts to guarantee a successful SS implementation.

Despite a vast body of literature in SS CSFs, this paper demonstrates those factors within a Brazilian context. Moreover, the tested content of this study fills the research gap by providing reliable and useful CSFs of SS implementation, which contributes to increase the external validity of the SS construct. On top of that, although the results reinforce the importance of well-known, traditional CSFs in SS implementation, they also identify contingent factors related to risk perception, which are barely mentioned in previous literature.