Expanding adoption of drinking water treatment systems in developing countries: a case study from Tamil Nadu, India

Household-level water treatment and safe storage systems (HWTS) are simple, local, user-friendly, and low cost options to improve drinking water quality at the point of use. However, despite conclusive evidence of the health and economic benefits of HWTS, and promotion efforts in over 50 countries in the past 20 years, implementation outcomes have been slow, reaching only 5-10 million regular users. This study attempts to understand the barriers and drivers affecting HWTS implementation. Using a case study example of a biosand filter program in southern India, system dynamics modelling is shown to be a useful tool to map the inter-relationships of different critical factors and to understand the dissemination dynamics. It is found that the co-existence of expanding quickly and achieving financial sustainability appears to be difficult to achieve under the current program structure.

Design for all: designing for the motion-impaired user

Designing for all requires the adaptation and modification of current design best practices to encompass a broader range of user capabilities. This is particularly the case in the design of the human-product interface. Product interfaces exist everywhere and when designing them, there is a very strong temptation to jump to prescribing a solution with only a cursory attempt to understand the nature of the problem. This is particularly the case when attempting to adapt existing designs, optimised for able-bodied users, for use by disabled users. However, such approaches have led to numerous products that are neither usable nor commercially successful. In order to develop a successful design approach it is necessary consider the fundamental structure of the design process being applied. A three stage design process development strategy which includes problem definition, solution development and solution evaluation, should be adopted. This paper describes the development of a new design approach based on the application of usability heuristics to the design of interfaces. This is illustrated by reference to a particular case study of the re-design of a computer interface for controlling an assistive device.

Design-phase-specific selection of user research methods

For increasing the usability of a medical device the usability engineering standards IEC 60601-1-6 and IEC 62366 suggest incorporating user information in the design and development process. However, practice shows that integrating user information and the related investigation of users, called user research, is difficult in the field of medical devices. In particular, identifying the most appropriate user research methods is a difficult process. This difficulty results from the complexity of the medical device industry, especially with respect to regulations and standards, the characteristics of this market and the broad range of potential user research methods available from various research disciplines. Against this background, this study aimed at guiding designers and engineers in selecting effective user research methods according to their stage in the design process. Two approaches are described which reduce the complexity of method selection by summarizing the high number of methods into homogenous method classes. These approaches are closely connected to the medical device industry characteristic design phases and therefore provide the possibility of selecting design-phase- specific user research methods. In the first approach potential user research methods are classified after their characteristics in the design process. The second approach suggests a method summarization according to their similarity in the data collection techniques and provides an additional linkage to design phase characteristics. Both approaches have been tested in practice and the results show that both approaches facilitate user research method selection. © 2009 Springer-Verlag.

Investigating the relationships between user capabilities and product demands for older and disabled users

This paper presents the results of a study that specifically looks at the relationships between measured user capabilities and product demands in a sample of older and disabled users. An empirical study was conducted with 19 users performing tasks with four consumer products (a clock-radio, a mobile phone, a blender and a vacuum cleaner). The sensory, cognitive and motor capabilities of each user were measured using objective capability tests. The study yielded a rich dataset comprising capability measures, product demands, outcome measures (task times and errors), and subjective ratings of difficulty. Scatter plots were produced showing quantified product demands on user capabilities, together with subjective ratings of difficulty. The results are analysed in terms of the strength of correlations observed taking into account the limitations of the study sample. Directions for future research are also outlined. © 2011 Springer-Verlag.

Data-based robust multiobjective optimization of interconnected processes: energy efficiency case study in papermaking.

Reducing energy consumption is a major challenge for "energy-intensive" industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of "optimized" operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method.

Data-based robust multiobjective optimization of interconnected processes: Energy efficiency case study in papermaking

Reducing energy consumption is a major challenge for energy-intensive industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of optimized operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method. © 2006 IEEE.