The impact of Six Sigma in the performance of a Pollution Prevention program

The diffusion of Pollution Prevention faces organizational barriers as for instance resistance to change, insufficient support from decision-makers, unclear project leadership, insufficient employee accountability and inflexible organizational structures. To understand how to overcome such barriers, the performance of a Pollution Prevention program of a multinational corporation is analyzed. The quantitative analyses of 2096 Pollution Prevention projects conducted between 1995 and 2007 support the conclusion that the performance of the Pollution Prevention program increased after the implementation of the Six Sigma program. Moreover, the analyses of 1906 Pollution Prevention projects and 31,133 Six Sigma projects for cost reduction in 27 countries indicate that in countries where the implementation of Six Sigma is more expressive, pollution is prevented more than in countries with less expressive Six Sigma implementation. In fact, the Six Sigma implementation improved the organizational capability for data based project management. Therefore, comparing six years before and six years after the Six Sigma implementation, the total number of Pollution Prevention projects recognized increased 6.9 times and the total amount of pollution prevented increased by 62%. The qualitative analysis describes how the Six Sigma program interacts with the Pollution Prevention program in the studied company.     

RAMS contribution to efficient waste minimisation and management

The significance of waste management systems in recent years increased due to the growing problems of waste management chains affecting the daily lives of millions of people and the impact on the environment. Several promising approaches have been developed in the past few years. One of them is the waste management system modelling using reliability, availability, maintainability and safety software. This paper analyses and evaluates this approach. The main goal is to provide quantitative forecasts for various performance measures of waste management systems. They include availability, downtimes, number of failures, and cost. Evaluation of these measures is important for optimal decision making. The system design should both maximise the system performance leading to cleaner processing and minimise the overall cost within the allowable constraints. The effectiveness of this methodology is demonstrated through a case study.