Using Key Performance Indicators for multi-criteria traffic management strategic decisions

In recent research work (FP7 CONDUITS) a performance evaluation framework for traffic management and Intelligent Transport Systems was developed. The new framework consists of a set of Key Performance Indicators (KPIs) for the strategic themes of traffic efficiency, safety, pollution reduction and social inclusion, and the last stages of the project saw its validation through its application to four case studies. Following up from this work, this paper presents the extension of the framework for use as a prediction tool enabling urban transport authorities to assess the impacts of relevant policies and technologies before implementing them. The first stage of the extension focused on pollution reduction, and a novel decision support tool (CONDUITS_DST) integrating the respective KPI with micro-simulation modelling was developed. Case studies executed in Brussels and Zurich demonstrated the usability and viability of the tool. This paper takes the development one step further and reports on the extension of the approach, which moves from single-criterion to a multi-criteria decision support tool through the inclusion of the KPI on traffic efficiency, again based onmicro-simulation modelling outputs

A Management Maturity Model (MMM) for project-based organisational performance assessment

Common sense suggests that organisations are more likely to deliver successful projects if they have systems in place that reflect a mature project environment based on a culture of continuous improvement. This paper develops and discusses a Management Maturity Model (MMM) to assess the maturity of project management organisations through a customisable, systematic, strategic and practical methodology inspired from the seminal work of Darwin, Deming, Drucker and Daniel. The model presented is relevant to organisations, such as construction and engineering companies, that prefer to use the Project Management Body of Knowledge (PMBOK™ Guide) published by the Project Management Institute (PMI), but without the disadvantages of excessive time and cost commitments and a ‘one size fits all’ approach linked to rigid increments of maturity. It offers a game-changing advance in the application of project-based organisational performance assessment compared to existing market solutions that are unnecessarily complex. The feasibility of MMM is field-tested using a medium-sized data centre infrastructure firm in Tehran

Analysis of Sector Led Improvement of Children and Young People’s Services

This paper was commissioned by the Association of Directors of Children’s Services (ADCS) National Performance and Information Management Group (NPIMG) to support the work of ADCS to evaluate and assess the impact of Sector Led Improvement of Children and Young People’s Services, and to explore the possibility of designing and developing (with ADCS and other partners) an ‘Early Warning’ model. The objective is to identify when and where the performance of Children and Young People’s Services is moving in the wrong direction. We undertake pre-post testing and difference in difference analysis, the latter allows us to use control data to ensure that external factors affecting all regions are considered

Maintenance Strategies to Reduce Downtime Due to Machine Positional Errors

Manufacturing strives to reduce waste and increase Overall Equipment Effectiveness (OEE). When managing machine tool maintenance a manufacturer must apply an appropriate decision technique in order to reveal hidden costs associated with production losses, reduce equipment downtime competently and similarly identify the machines’ performance. Total productive maintenance (TPM) is a maintenance program that involves concepts for maintaining plant and equipment effectively. OEE is a powerful metric of manufacturing performance incorporating measures of the utilisation, yield and efficiency of a given process, machine or manufacturing line. It supports TPM initiatives by accurately tracking progress towards achieving “perfect production.” This paper presents a review of maintenance management methodologies and their application to positional error calibration decision-making. The purpose of this review is to evaluate the contribution of maintenance strategies, in particular TPM, towards improving manufacturing performance, and how they could be applied to reduce downtime due to inaccuracy of the machine. This is to find a balance between predictive calibration, on-machine checking and lost production due to inaccuracy. This work redefines the role of maintenance management techniques and develops a framework to support the process of implementing a predictive calibration program as a prime method to supporting the change of philosophy for machine tool calibration decision making. Keywords—maintenance strategies, down time, OEE, TPM, decision making, predictive calibration

Framework for continuous improvement of production processes

This research introduces a new approach of using Six Sigma DMAIC (Define, Measure, Analyse, Improve, Control) methodology. This approach integrates various tools and methods into a single framework, which consists of five steps. In the Define step, problems and main Key Performance Indicators (KPIs) are identified. In the Measure step, the modified Failure Classifier (FC), i.e. DOE-NE-STD-1004-92 is applied, which enables to specify the types of failures for each operation during the production process. Also, Failure Mode and Effect Analysis (FMEA) is used to measure the weight of failures by calculating the Risk Priority Number (RPN) value. In order to indicate the quality level of process/product the Process/Product Sigma Performance Level (PSPL) is calculated based on the FMEA results. Using the RPN values from FMEA the variability of process by failures, operations and work centres are observed. In addition, costs of the components are calculated, which enable to measure the impact of failures on the final product cost. A new method of analysis is introduced, in which various charts created in the Measure step are compared. Analysis step facilitates the subsequent Improve and Control steps, where appropriate changes in the manufacturing process are implemented and sustained. The objective of the new framework is to perform continuous improvement of production processes in the way that enables engineers to discover the critical problems that have financial impact on the final product. This framework provides new ways of monitoring and eliminating failures for production processes continuous improvement, by focusing on the KPIs important for business success. In this paper, the background and the key concepts of Six Sigma are described and the proposed Six Sigma DMAIC framework is explained. The implementation of this framework is verified by computational experiment followed by conclusion section

Fostering collective intelligence education

New educational models are necessary to update learning environments to the digitally shared communication and information. Collective intelligence is an emerging field that already has a significant impact in many areas and will have great implications in education, not only from the side of new methodologies but also as a challenge for education. This paper proposes an approach to a collective intelligence model of teaching using Internet to combine two strategies: idea management and real time assessment in the class. A digital tool named Fabricius has been created supporting these two elements to foster the collaboration and engagement of students in the learning process. As a result of the research we propose a list of KPI trying to measure individual and collective performance. We are conscious that this is just a first approach to define which aspects of a class following a course can be qualified and quantified.Postprint (published version