Using the Summed Rank Cusum for monitoring environmental data from industrial processes

Environmental issues have become a hot topic recently, especially those surrounding industrial outputs. Effluents, emissions, outflows, by-products, waste materials, product de-commissioning, land reclamation and energy consumption are all the subject of monitoring, either under new legislation or through economic necessity. Many types of environmental data are often difficult to understand or measure because of their unusual distribution of values however. Standard methods of monitoring these data types often fail or are unwieldy. The scarcity of events, small volume measurements and the unusual time scales sometimes involved add to the complexity of the task. One recently developed monitoring technique is the Summed Rank Cusum (SRC) that applies non-parametric methods to a standard chart. The SRC can be used diagnostically and this paper describes the application of this new tool to three data sets, each derived from a different problem area. These are measuring industrial effluent, assessing the levels of potentially harmful proteins produced by an industrial process and industrial land reclamation in the face of harmful waste materials. The use of the SRC to spot change points in time retrospectively is described. The paper also shows the use of SRC in the significant-difference testing mode, which is applied via the use of spreadsheets. Links to other similar methods described in the literature are given and formulae describing the statistical nature of the transformation are shown. These practical demonstrations illustrate that the graphical interpretation of the method appears to help considerably in practice when trying to find time-series change points. The charts are an effective graphical retrospective monitoring technique when dealing with non-normal data. The method is easy to apply and may help considerably in dealing with environmental data in the industrial setting when standard methods are not appropriate. Further work is continuing on the more theoretical aspects of the method.     

Improving communication via quantitative management

Villa Soft Drinks Ltd, established in 1884, manufactures and bottles spring waters and carbonates for both the growing adult soft drinks market and the more traditional soft drinks market. The company employs just over 100 people split between the manufacturing site in Sunderland and the head office and distribution centre in Washington. One of the fundamental problems affecting the day-to-day running of Villa, and most companies, is communication. There is a lack of awareness of the impact that changes in one department have on other departments (e.g. if production efficiency is increased by 10%, what impact will this have on warehousing?). Villa had recently identified key performance indicators (KPIs) to monitor all aspects of manufacturing performance on a regular basis. This enabled the current production situation to be evaluated and helped familiarize staff with charts and measurements. The use of Pareto analysis and problem solving techniques helped to boost efficiency and utilization. Key performance indicators were then developed in most other departments and are monitored and displayed regularly. The KPIs can be used further to improve transparency across the company by incorporating them in an interactive, interpretative tool to aid communication and understanding at all levels of the company. Individual departmental flow diagrams will be linked together to represent how the company operates. The diagrams will include both material flow and information flow. These data will then be organized in a software package and the end result will be a fully integrated simulation of the company in which any variable can be altered to demonstrate the effect this has on other departments and therefore the company as a whole. This will be an extremely valuable tool for the company as it will have many different applications, such as calculating manning requirements, identifying potential cycle time reductions and optimizing warehouse space.     

Development and Social Problems: The Impact of the Offshore Oil Industry on Suicide and Homicide Rates1

Abstract There are few studies in the literature concerning economic development that examine the impact of offshore oil and gas extraction on communities and even fewer that use annual data, examine more than one community and account for the degree of involvement of the community in the oil industry. This study rectifies these problems. The results support hypotheses derived from social disorganization and relative deprivation theories by demonstrating that higher levels of and rapid changes in development are associated with higher homicide and suicide rates, especially in communities that are more involved in resource extraction. The utility of the methods and the implications of the results for theory and future research are discussed.