Measurement and compensation of pivot point positional error on five-axis machines

Measuring and compensating the pivot points of five-axis machine tools is always challenging and very time consuming. This paper presents a newly developed approach for automatic measurement and compensation of pivot point positional errors on five-axis machine tools. Machine rotary axis errors are measured using a circular test. This method has been tested on five-axis machine tools with swivel table configuration. Results show that up to 99% of the positional errors of the rotary axis can be compensated by using this approach.

The impact of supply chain performance measurement systems on dynamic behaviour in supply chains

The amplification of demand variation up a supply chain widely termed ‘the Bullwhip Effect’ is disruptive, costly and something that supply chain management generally seeks to minimise. Originally attributed to poor system design; deficiencies in policies, organisation structure and delays in material and information flow all lead to sub-optimal reorder point calculation. It has since been attributed to exogenous random factors such as: uncertainties in demand, supply and distribution lead time but these causes are not exclusive as academic and operational studies since have shown that orders and/or inventories can exhibit significant variability even if customer demand and lead time are deterministic. This increase in the range of possible causes of dynamic behaviour indicates that our understanding of the phenomenon is far from complete. One possible, yet previously unexplored, factor that may influence dynamic behaviour in supply chains is the application and operation of supply chain performance measures. Organisations monitoring and responding to their adopted key performance metrics will make operational changes and this action may influence the level of dynamics within the supply chain, possibly degrading the performance of the very system they were intended to measure. In order to explore this a plausible abstraction of the operational responses to the Supply Chain Council’s SCOR® (Supply Chain Operations Reference) model was incorporated into a classic Beer Game distribution representation, using the dynamic discrete event simulation software Simul8. During the simulation the five SCOR Supply Chain Performance Attributes: Reliability, Responsiveness, Flexibility, Cost and Utilisation were continuously monitored and compared to established targets. Operational adjustments to the; reorder point, transportation modes and production capacity (where appropriate) for three independent supply chain roles were made and the degree of dynamic behaviour in the Supply Chain measured, using the ratio of the standard deviation of upstream demand relative to the standard deviation of the downstream demand. Factors employed to build the detailed model include: variable retail demand, order transmission, transportation delays, production delays, capacity constraints demand multipliers and demand averaging periods. Five dimensions of supply chain performance were monitored independently in three autonomous supply chain roles and operational settings adjusted accordingly. Uniqueness of this research stems from the application of the five SCOR performance attributes with modelled operational responses in a dynamic discrete event simulation model. This project makes its primary contribution to knowledge by measuring the impact, on supply chain dynamics, of applying a representative performance measurement system.

The impact of performance measurement in strategic planning

Purpose – To investigate the impact of performance measurement in strategic planning process. Design/methodology/approach – A large scale survey was conducted online with Warwick Business School alumni. The questionnaire was based on the Strategic Development Process model by Dyson. The questionnaire was designed to map the current practice of strategic planning and to determine its most influential factors on the effectiveness of the process. All questions were close ended and a seven-point Likert scale used. The independent variables were grouped into four meaningful factors by factor analysis (Varimax, coefficient of rotation 0.4). The factors produced were used to build regression models (stepwise) for the five assessments of strategic planning process. Regression models were developed for the totality of the responses, comparing SMEs and large organizations and comparing organizations operating in slowly and rapidly changing environments. Findings – The results indicate that performance measurement stands as one of the four main factors characterising the current practice of strategic planning. This research has determined that complexity coming from organizational size and rate of change in the sector creates variation in the impact of performance measurement in strategic planning. Large organizations and organizations operating in rapidly changing environments make greater use of performance measurement. Research limitations/implications – This research is based on subjective data, therefore the conclusions do not concern the impact of strategic planning process' elements on the organizational performance achievements, but on the success/effectiveness of the strategic planning process itself. Practical implications – This research raises a series of questions about the use and potential impact of performance measurement, especially in the categories of organizations that are not significantly influenced by its utilisation. It contributes to the field of performance measurement impact. Originality/value – This research fills in the gap literature concerning the lack of large scale surveys on strategic development processes and performance measurement. It also contributes in the literature of this field by providing empirical evidences on the impact of performance measurement upon the strategic planning process.

Fibre optics sensors in tear electrolyte analysis:towards a novel point of care potassium sensor

The diagnosis of ocular disease is increasingly important in optometric practice and there is a need for cost effective point of care assays to assist in that. Although tears are a potentially valuable source of diagnostic information difficulties associated with sample collection and limited sample size together with sample storage and transport have proved major limitations. Progressive developments in electronics and fibre optics together with innovation in sensing technology mean that the construction of inexpensive point of care fibre optic sensing devices is now possible. Tear electrolytes are an obvious family of target analytes, not least to complement the availability of devices that make the routine measurement of tear osmolarity possible in the clinic. In this paper we describe the design, fabrication and calibration of a fibre-optic based electrolyte sensor for the quantification of potassium in tears using the ex vivo contact lens as the sample source. The technology is generic and the same principles can be used in the development of calcium and magnesium sensors. An important objective of this sensor technology development is to provide information at the point of routine optometric examination, which would provide supportive evidence of tear abnormality.

Temperature-referenced high-sensitivity point-probe optical fiber chem-sensors based on cladding etched fiber Bragg gratings

Point-probe optical fiber chem-sensors have been implemented using cladding etched fiber Bragg gratings. The sensors possess refractive index sensing capability that can be utilized to measure chemical concentrations. The Bragg wavelength shift reaches 8 nm when the index of surrounding medium changes from 1.33 to 1.44, giving maximum sensitivity more than 10 times higher than that of previously reported devices. More importantly, the dual-grating configuration of the point-probe sensors offers a temperature reference function, permitting accurate measurement of refractive index encoded chemical concentrations.

Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector

Guest editorial Ali Emrouznejad is a Senior Lecturer at the Aston Business School in Birmingham, UK. His areas of research interest include performance measurement and management, efficiency and productivity analysis as well as data mining. He has published widely in various international journals. He is an Associate Editor of IMA Journal of Management Mathematics and Guest Editor to several special issues of journals including Journal of Operational Research Society, Annals of Operations Research, Journal of Medical Systems, and International Journal of Energy Management Sector. He is in the editorial board of several international journals and co-founder of Performance Improvement Management Software. William Ho is a Senior Lecturer at the Aston University Business School. Before joining Aston in 2005, he had worked as a Research Associate in the Department of Industrial and Systems Engineering at the Hong Kong Polytechnic University. His research interests include supply chain management, production and operations management, and operations research. He has published extensively in various international journals like Computers & Operations Research, Engineering Applications of Artificial Intelligence, European Journal of Operational Research, Expert Systems with Applications, International Journal of Production Economics, International Journal of Production Research, Supply Chain Management: An International Journal, and so on. His first authored book was published in 2006. He is an Editorial Board member of the International Journal of Advanced Manufacturing Technology and an Associate Editor of the OR Insight Journal. Currently, he is a Scholar of the Advanced Institute of Management Research. Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector This special issue aims to focus on holistic, applied research on performance measurement in energy sector management and for publication of relevant applied research to bridge the gap between industry and academia. After a rigorous refereeing process, seven papers were included in this special issue. The volume opens with five data envelopment analysis (DEA)-based papers. Wu et al. apply the DEA-based Malmquist index to evaluate the changes in relative efficiency and the total factor productivity of coal-fired electricity generation of 30 Chinese administrative regions from 1999 to 2007. Factors considered in the model include fuel consumption, labor, capital, sulphur dioxide emissions, and electricity generated. The authors reveal that the east provinces were relatively and technically more efficient, whereas the west provinces had the highest growth rate in the period studied. Ioannis E. Tsolas applies the DEA approach to assess the performance of Greek fossil fuel-fired power stations taking undesirable outputs into consideration, such as carbon dioxide and sulphur dioxide emissions. In addition, the bootstrapping approach is deployed to address the uncertainty surrounding DEA point estimates, and provide bias-corrected estimations and confidence intervals for the point estimates. The author revealed from the sample that the non-lignite-fired stations are on an average more efficient than the lignite-fired stations. Maethee Mekaroonreung and Andrew L. Johnson compare the relative performance of three DEA-based measures, which estimate production frontiers and evaluate the relative efficiency of 113 US petroleum refineries while considering undesirable outputs. Three inputs (capital, energy consumption, and crude oil consumption), two desirable outputs (gasoline and distillate generation), and an undesirable output (toxic release) are considered in the DEA models. The authors discover that refineries in the Rocky Mountain region performed the best, and about 60 percent of oil refineries in the sample could improve their efficiencies further. H. Omrani, A. Azadeh, S. F. Ghaderi, and S. Abdollahzadeh presented an integrated approach, combining DEA, corrected ordinary least squares (COLS), and principal component analysis (PCA) methods, to calculate the relative efficiency scores of 26 Iranian electricity distribution units from 2003 to 2006. Specifically, both DEA and COLS are used to check three internal consistency conditions, whereas PCA is used to verify and validate the final ranking results of either DEA (consistency) or DEA-COLS (non-consistency). Three inputs (network length, transformer capacity, and number of employees) and two outputs (number of customers and total electricity sales) are considered in the model. Virendra Ajodhia applied three DEA-based models to evaluate the relative performance of 20 electricity distribution firms from the UK and the Netherlands. The first model is a traditional DEA model for analyzing cost-only efficiency. The second model includes (inverse) quality by modelling total customer minutes lost as an input data. The third model is based on the idea of using total social costs, including the firm’s private costs and the interruption costs incurred by consumers, as an input. Both energy-delivered and number of consumers are treated as the outputs in the models. After five DEA papers, Stelios Grafakos, Alexandros Flamos, Vlasis Oikonomou, and D. Zevgolis presented a multiple criteria analysis weighting approach to evaluate the energy and climate policy. The proposed approach is akin to the analytic hierarchy process, which consists of pairwise comparisons, consistency verification, and criteria prioritization. In the approach, stakeholders and experts in the energy policy field are incorporated in the evaluation process by providing an interactive mean with verbal, numerical, and visual representation of their preferences. A total of 14 evaluation criteria were considered and classified into four objectives, such as climate change mitigation, energy effectiveness, socioeconomic, and competitiveness and technology. Finally, Borge Hess applied the stochastic frontier analysis approach to analyze the impact of various business strategies, including acquisition, holding structures, and joint ventures, on a firm’s efficiency within a sample of 47 natural gas transmission pipelines in the USA from 1996 to 2005. The author finds that there were no significant changes in the firm’s efficiency by an acquisition, and there is a weak evidence for efficiency improvements caused by the new shareholder. Besides, the author discovers that parent companies appear not to influence a subsidiary’s efficiency positively. In addition, the analysis shows a negative impact of a joint venture on technical efficiency of the pipeline company. To conclude, we are grateful to all the authors for their contribution, and all the reviewers for their constructive comments, which made this special issue possible. We hope that this issue would contribute significantly to performance improvement of the energy sector.

Temperature-referenced high-sensitivity point-probe optical fiber chem-sensors based on cladding etched fiber Bragg gratings

Point-probe optical fiber chem-sensors have been implemented using cladding etched fiber Bragg gratings. The sensors possess refractive index sensing capability that can be utilized to measure chemical concentrations. The Bragg wavelength shift reaches 8 nm when the index of surrounding medium changes from 1.33 to 1.44, giving maximum sensitivity more than 10 times higher than that of previously reported devices. More importantly, the dual-grating configuration of the point-probe sensors offers a temperature reference function, permitting accurate measurement of refractive index encoded chemical concentrations.

Climate change performance measurement, control and accountability in English local areas

Purpose – This paper aims to consider how climate change performance is measured and accounted for within the performance framework for local authority areas in England adopted in 2008. It critically evaluates the design of two mitigation and one adaptation indicators that are most relevant to climate change. Further, the potential for these performance indicators to contribute to climate change mitigation and adaptation is discussed. Design/methodology/approach – The authors begin by examining the importance of the performance framework and the related Local Area Agreements (LAAs), which were negotiated for all local areas in England between central government and Local Strategic Partnerships (LSPs). This development is located within the broader literature relating to new public management. The potential for this framework to assist in delivering the UK's climate change policy objectives is researched in a two-stage process. First, government publications and all 150 LAAs were analysed to identify the level of priority given to the climate change indicators. Second, interviews were conducted in spring 2009 with civil servants and local authority officials from the English West Midlands who were engaged in negotiating the climate change content of the LAAs. Findings – Nationally, the authors find that 97 per cent of LAAs included at least one climate change indicator as a priority. The indicators themselves, however, are perceived to be problematic – in terms of appropriateness, accuracy and timeliness. In addition, concerns were identified about the level of local control over the drivers of climate change performance and, therefore, a question is raised as to how LSPs can be held accountable for this. On a more positive note, for those concerned about climate change, the authors do find evidence that the inclusion of these indicators within the performance framework has helped to move climate change up the agenda for local authorities and their partners. However, actions by the UK's new coalition government to abolish the national performance framework and substantially reduce public expenditure potentially threaten this advance. Originality/value – This paper offers an insight into a new development for measuring climate change performance at a local level, which is relatively under-researched. It also contributes to knowledge of accountability within a local government setting and provides a reference point for further research into the potential role of local actions to address the issue of climate change.

Power industry restructuring and eco-efficiency changes:a new slacks-based model in Malmquist-Luenberger Index measurement

Measuring variations in efficiency and its extension, eco-efficiency, during a restructuring period in different industries has always been a point of interest for regulators and policy makers. This paper assesses the impacts of restructuring of procurement in the Iranian power industry on the performance of power plants. We introduce a new slacks-based model for Malmquist-Luenberger (ML) Index measurement and apply it to the power plants to calculate the efficiency, eco-efficiency, and technological changes over the 8-year period (2003-2010) of restructuring in the power industry. The results reveal that although the restructuring had different effects on the individual power plants, the overall growth in the eco-efficiency of the sector was mainly due to advances in pure technology. We also assess the correlation between efficiency and eco-efficiency of the power plants, which indicates a close relationship between these two steps, thus lending support to the incorporation of environmental factors in efficiency analysis. © 2014 Elsevier Ltd.

Measurement of residual stress by load and depth sensing indentation with spherical indenters

A new experimental technique is presented for making measurements of biaxial residual stress using load and depth sensing indentation (nanoindentation). The technique is based on spherical indentation, which, in certain deformation regimes, can be much more sensitive to residual stress than indentation with sharp pyramidal indenters like the Berkovich. Two different methods of analysis were developed: one requiring an independent measure of the material's yield strength and the other a reference specimen in the unstressed state or other known reference condition. Experiments conducted on aluminum alloys to which controlled biaxial bending stresses were applied showed that the methods are capable of measuring the residual stress to within 10-20% of the specimen yield stress. Because the methods do not require imaging of the hardness impressions, they are potentially useful for making localized measurements of residual stress, as in thin films or small volumes, or for characterization of point-to-point spatial variations of the surface stress.

Phase-shifted fiber Bragg grating for strain measurement at extreme conditions

In this work, a phase-shifted fiber Bragg grating is proposed for strain sensing at extreme temperatures. The grating structure is written in bare standard single mode fiber, using the point-by-point femtosecond laser technique. Strain measurements are performed at temperatures ranging from room temperature up to 900°C. By subjecting the sensor to such extreme conditions, the wavelength of the grating increases. © 2014 OSA.

Measurement and correlation of the solubility of telmisartan (form A) in nine different solvents from 277.85 to 338.35 K

The solubility of telmisartan (form A) in nine organic solvents (chloroform, dichloromethane, ethanol, toluene, benzene, 2-propanol, ethyl acetate, methanol and acetone) was determined by a laser monitoring technique at temperatures from 277.85 to 338.35 K. The solubility of telmisartan (form A) in all of the nine solvents increased with temperature as did the rates at which the solubility increased except in chloroform and dichloromethane. The mole fraction solubility in chloroform is higher than that in dichloromethane, which are both one order of magnitude higher than those in the other seven solvents at the experimental temperatures. The solubility data were correlated with the modified Apelblat equation and λh equations. The results show that the λh equation is in better agreement with the experimental data than the Apelblat equation. The relative root mean square deviations (σ) of the λh equation are in the range from 0.004 to 0.45 %. The dissolution enthalpies, entropies and Gibbs energies of telmisartan in these solvents were estimated by the Van’t Hoff equation and the Gibbs equation. The melting point and the fusion enthalpy of telmisartan were determined by differential scanning calorimetry.