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Some (non)manufacturing industries are becoming more energy efficient, but many of them are losing cost-effective energy-savings opportunities, namely, by lack of knowledge or underestimation of good engineering and management practices as well as guidance on techniques or tools for that purpose. This study points out that Design of Experiments is a tool that cannot be ignored by managers and other technical staff, namely, by those who have the responsibility to eliminate energy waste and promote energy-efficiency improvement in industry, mainly in energy-intensive manufacturing industries. A review on Design of Experiments for physical and simulation experiments, supported on carefully selected references, is provided, since process and product improvement at the design and manufacturing stages increasingly rely on virtual tests and digital simulations. However, the expense of running experiments in complex computer models is still a relevant issue, despite advances in computer hardware and software capabilities. Here, experiments were statistically designed, and several easy-to-implement yet effective data analysis methods were employed for identifying the variables that must be measured with more accurate devices and methods to better estimate the energy efficiency or improve it in a billets reheating furnace. A simulation model of this type of furnace was used to run the experiments and the results analysis shows that variables with practical effect on the furnace’s energy efficiency are the percentage of oxygen in the combustion gases, the fuel flow in the burners, and the combustion air temperature.
Nuno Costa; Paulo Fontes. Energy-Efficiency Assessment and Improvement—Experiments and Analysis Methods. Sustainability 2020, 12, 7603 .
AMA StyleNuno Costa, Paulo Fontes. Energy-Efficiency Assessment and Improvement—Experiments and Analysis Methods. Sustainability. 2020; 12 (18):7603.
Chicago/Turabian StyleNuno Costa; Paulo Fontes. 2020. "Energy-Efficiency Assessment and Improvement—Experiments and Analysis Methods." Sustainability 12, no. 18: 7603.
Purpose The purpose of this paper is to address misconceptions about the design of experiments (DoE) usefulness, avoid bad practices and foster processes’ efficiency and products’ quality in a timely and cost-effective manner with this tool. Design/methodology/approach To revisit and discuss the hindrances to DoE usage as well as bad practices in using this tool supported on the selective literature from Web of Science and Scopus indexed journals. Findings A set of recommendations and guidelines to mitigate DoE hindrances and avoid common errors or wrong decisions at the planning, running and data analysis phases of DoE are provided. Research limitations/implications Errors or wrong decisions in planning, running and analyzing data from statistically designed experiments are always possible so the expected results from DoE usage are not always 100 percent guaranteed. Practical implications Novice and intermediate DoE users have another perspective for developing and improving their “test and learn” capability and be successful with DoE. To appropriately plan and run statistically designed experiments not only save the user of DoE from incorrect decisions and depreciation of their technical competencies as they can optimize processes’ efficiency and products’ quality (reliability, durability, performance, robustness, etc.) in a structured, faster and cheaper way at the design and manufacturing stages. Social implications DoE usefulness will be increasingly recognized in industry and academy and, as consequence, better products can be made available for consumers, business performance can improve, and the link between industry and academy can be strengthened. Originality/value A supplemental perspective on how to succeed with DoE and foster its usage among managers, engineers and other technical staff is presented.
Nuno Costa. Design of experiments – overcome hindrances and bad practices. The TQM Journal 2019, 31, 772 -789.
AMA StyleNuno Costa. Design of experiments – overcome hindrances and bad practices. The TQM Journal. 2019; 31 (5):772-789.
Chicago/Turabian StyleNuno Costa. 2019. "Design of experiments – overcome hindrances and bad practices." The TQM Journal 31, no. 5: 772-789.
For a reasoned decision-making in multiresponse problems, it is important to investigate how consistent the Pareto Frontier is to responses estimation uncertainty. To investigate the impact of this uncertainty source on the Pareto frontier, solutions achieved from the worst and mean responses estimate were generated and compared. Results are displayed graphically and a metric is used to select an optimal solution.
Nuno Costa; João Lourenço. Worst-case Responses Estimate Impact on Pareto Front. DEStech Transactions on Engineering and Technology Research 2017, 1 .
AMA StyleNuno Costa, João Lourenço. Worst-case Responses Estimate Impact on Pareto Front. DEStech Transactions on Engineering and Technology Research. 2017; (amsm):1.
Chicago/Turabian StyleNuno Costa; João Lourenço. 2017. "Worst-case Responses Estimate Impact on Pareto Front." DEStech Transactions on Engineering and Technology Research , no. amsm: 1.
Nuno Costa; João Lourenço. Reproducibility of nondominated solutions. Chemometrics and Intelligent Laboratory Systems 2017, 168, 1 -9.
AMA StyleNuno Costa, João Lourenço. Reproducibility of nondominated solutions. Chemometrics and Intelligent Laboratory Systems. 2017; 168 ():1-9.
Chicago/Turabian StyleNuno Costa; João Lourenço. 2017. "Reproducibility of nondominated solutions." Chemometrics and Intelligent Laboratory Systems 168, no. : 1-9.
MATEC Web of Conferences, open access proceedings in Materials science, Engineering and Chemistry
Nuno Costa; João Lourenço. Responses’ Prediction Standard Error Analysis in Pareto Solutions. MATEC Web of Conferences 2017, 108, 10007 .
AMA StyleNuno Costa, João Lourenço. Responses’ Prediction Standard Error Analysis in Pareto Solutions. MATEC Web of Conferences. 2017; 108 ():10007.
Chicago/Turabian StyleNuno Costa; João Lourenço. 2017. "Responses’ Prediction Standard Error Analysis in Pareto Solutions." MATEC Web of Conferences 108, no. : 10007.
A diversity of multiresponse optimization methods has been introduced in the literature; however, their performance has not been thoroughly explored, and only a classical desirability-based criterion has been commonly used. With the aim of contributing to help practitioners in selecting an effective criterion for solving multiresponse optimization problems developed under the response surface methodology framework, and thus to find compromise solutions that are technically and economically more favorable, the working ability of several easy-to-use criteria is evaluated and compared with that of a theoretically sound method. Four case studies with different numbers and types of responses are considered. Less-sophisticated criteria were able to generate solutions similar to those generated by sophisticated methods, even when the objective is to depict the Pareto frontier in problems with conflicting responses. Two easy-to-use criteria that require less-subjective information from the user yielded solutions similar to those of a classical desirability-based criterion. Preference parameters range and increment impact on optimal solutions were also evaluated.
Nuno Ricardo Costa; João Lourenço. Multiresponse problems: desirability and other optimization approaches. Journal of Chemometrics 2016, 30, 702 -714.
AMA StyleNuno Ricardo Costa, João Lourenço. Multiresponse problems: desirability and other optimization approaches. Journal of Chemometrics. 2016; 30 (12):702-714.
Chicago/Turabian StyleNuno Ricardo Costa; João Lourenço. 2016. "Multiresponse problems: desirability and other optimization approaches." Journal of Chemometrics 30, no. 12: 702-714.
Response surface methodology was employed to optimize the efficiency of a refrigeration cycle demonstration unit using a multiresponse optimization approach. Statistically designed experiments were conducted to simultaneously minimize energy consumption and maximize the refrigeration effect of a compression refrigeration cycle. Regression models were fitted to refrigeration and electrical powers and optimal variable settings were identified using an easy-to-use optimization criterion. Results give confidence to apply the illustrated approach in academic and industrial settings, namely for optimizing equipment operation.
Nuno Ricardo Costa; João Garcia. Using a multiple response optimization approach to optimize the coefficient of performance. Applied Thermal Engineering 2016, 96, 137 -143.
AMA StyleNuno Ricardo Costa, João Garcia. Using a multiple response optimization approach to optimize the coefficient of performance. Applied Thermal Engineering. 2016; 96 ():137-143.
Chicago/Turabian StyleNuno Ricardo Costa; João Garcia. 2016. "Using a multiple response optimization approach to optimize the coefficient of performance." Applied Thermal Engineering 96, no. : 137-143.
Nuno Ricardo Costa; João Lourenço. Gaussian Process Model - An Exploratory Study in the Response Surface Methodology. Quality and Reliability Engineering International 2015, 32, 2367 -2380.
AMA StyleNuno Ricardo Costa, João Lourenço. Gaussian Process Model - An Exploratory Study in the Response Surface Methodology. Quality and Reliability Engineering International. 2015; 32 (7):2367-2380.
Chicago/Turabian StyleNuno Ricardo Costa; João Lourenço. 2015. "Gaussian Process Model - An Exploratory Study in the Response Surface Methodology." Quality and Reliability Engineering International 32, no. 7: 2367-2380.
Refrigeration cycles are used in a large diversity of industrial and domestic (residential and non-residential) equipment and their efficiency depend on several variables. To better understanding of how controllable variables impact on a compression refrigeration cycle efficiency, statistically designed experiments were conducted and data were analyzed. A quadratic polynomial model was fitted to Coefficient of Performance and variable settings to maximize cycle efficiency identified. Results give confidence to use the illustrated approach for refrigeration cycle design and operation improvement purposes
Nuno Ricardo Costa; João Garcia. Applying design of experiments to a compression refrigeration cycle. Cogent Engineering 2015, 2, 1 .
AMA StyleNuno Ricardo Costa, João Garcia. Applying design of experiments to a compression refrigeration cycle. Cogent Engineering. 2015; 2 (1):1.
Chicago/Turabian StyleNuno Ricardo Costa; João Garcia. 2015. "Applying design of experiments to a compression refrigeration cycle." Cogent Engineering 2, no. 1: 1.
Four multiresponse optimisation problems were simulated under the RSM framework to represent real-life situations and provide a fair basis to compare the performance of optimisation criteria built on different approaches. Different response types, feasible regions, number of responses and variables as well as adverse variance conditions were considered in each problem. An unusual graphical representation of the results provides useful information about working abilities of tested criteria. To help decision-maker in making more informed decisions about solution selection, performance metrics usefulness is also illustrated.
Nuno Costa; Joao Lourenço. Simulation of real-life situations in multiresponse problems: a contribution to criteria evaluation in the RSM framework. International Journal of Operational Research 2015, 23, 1 .
AMA StyleNuno Costa, Joao Lourenço. Simulation of real-life situations in multiresponse problems: a contribution to criteria evaluation in the RSM framework. International Journal of Operational Research. 2015; 23 (1):1.
Chicago/Turabian StyleNuno Costa; Joao Lourenço. 2015. "Simulation of real-life situations in multiresponse problems: a contribution to criteria evaluation in the RSM framework." International Journal of Operational Research 23, no. 1: 1.
Multiple response optimization problems have many optimal solutions that impact differently on process or product. Some of these solutions lead to operation conditions more hazardous, more costly or more difficult to implement and control. Therefore, it is useful for the decision-maker to use methods capable of capturing solutions evenly distributed along the Pareto frontier. Three examples were used to evaluate the ability of three methods built on different approaches for depicting the Pareto frontier. Limitations of a desirability-based method are illustrated whereas the consistent performance of an easy-to-use global criterion gives confidence to use it in real-life problems developed under the Response Surface Methodology framework, as alternative to the sophisticated physical programming method.
Nuno Ricardo Costa; João Alves Lourenço. Exploring Pareto Frontiers in the Response Surface Methodology. Transactions on Engineering Technologies 2015, 399 -412.
AMA StyleNuno Ricardo Costa, João Alves Lourenço. Exploring Pareto Frontiers in the Response Surface Methodology. Transactions on Engineering Technologies. 2015; ():399-412.
Chicago/Turabian StyleNuno Ricardo Costa; João Alves Lourenço. 2015. "Exploring Pareto Frontiers in the Response Surface Methodology." Transactions on Engineering Technologies , no. : 399-412.
Methods to solve multi-response problems developed under the RSM framework are rarely evaluated in terms of their ability to depict Pareto frontiers and their solutions do not provide information about response properties. This manuscript contributes for positioning some optimisation methods in relation to each other based on their ability to capture solutions in convex and non-convex surfaces in addition to the robustness, quality of predictions and bias of the generated solutions. Results show that an appealing compromise programming-based method can compete with leading methods in the field. It does not require preference information from the decision-maker, is easy-to-implement, can generate solutions to satisfy decision-makers with different sensitivity to bias and variance based on performance metric values, and evenly distributed solutions along the Pareto frontier. The validity of these results is supported on three examples.
Nuno Costa; Joao Lourenzo. On the generation and selection of solutions to multiple response problems. International Journal of Industrial and Systems Engineering 2015, 20, 437 .
AMA StyleNuno Costa, Joao Lourenzo. On the generation and selection of solutions to multiple response problems. International Journal of Industrial and Systems Engineering. 2015; 20 (4):437.
Chicago/Turabian StyleNuno Costa; Joao Lourenzo. 2015. "On the generation and selection of solutions to multiple response problems." International Journal of Industrial and Systems Engineering 20, no. 4: 437.
Nuno Costa; Joao Lourenco. A comparative study of multiresponse optimization criteria working ability. Chemometrics and Intelligent Laboratory Systems 2014, 138, 171 -177.
AMA StyleNuno Costa, Joao Lourenco. A comparative study of multiresponse optimization criteria working ability. Chemometrics and Intelligent Laboratory Systems. 2014; 138 ():171-177.
Chicago/Turabian StyleNuno Costa; Joao Lourenco. 2014. "A comparative study of multiresponse optimization criteria working ability." Chemometrics and Intelligent Laboratory Systems 138, no. : 171-177.
Separation of the few control factors with significant effect from the remaining ones at the early phase of experimental studies is a recommended practice for systems development and improvement. The normal probability plot is a widely accepted graphical technique for screening, although it does not provide a unique interpretation of results in some cases. Thus, more formal procedures have been proposed to supplement it. The performance of popular methods along with lesser known and used ones is assessed using four evaluation standards based on a simulation study. The results show that Al-Shiha and Yang's method stands out as the best performer when compared with other computational methods so it is the best choice to supplement the often used graphical technique. A strategy for analysing unreplicated fractional factorial designs is also outlined.
Nuno Costa; José Palma; Zulema Lopes Pereira. On the selection of significant variables from unreplicated factorial designs. International Journal of Productivity and Quality Management 2013, 12, 161 .
AMA StyleNuno Costa, José Palma, Zulema Lopes Pereira. On the selection of significant variables from unreplicated factorial designs. International Journal of Productivity and Quality Management. 2013; 12 (2):161.
Chicago/Turabian StyleNuno Costa; José Palma; Zulema Lopes Pereira. 2013. "On the selection of significant variables from unreplicated factorial designs." International Journal of Productivity and Quality Management 12, no. 2: 161.
Responses modeling and optimization criteria impact on the optimization results were investigated. The Ordinary Least Squares and Seemingly Unrelated Regression techniques were illustrated in two examples from the literature and the performance of three optimization criteria evaluated. In contrast to the standard practice, compromise solutions were evaluated in terms of bias and robustness using optimization performance measures. The results of both examples show that responses modeling strongly impacts on the optimization results, while there is no significant difference between criteria performance. The Seemingly Unrelated Regression technique proved to be useful for modeling correlated responses. Otherwise, this technique can lead to results in close agreement to those obtained with models fitted with the OLS technique.
Nuno Costa; Joao Lourenco; Zulema Lopes Pereira. Responses modeling and optimization criteria impact on the optimization of multiple quality characteristics. Computers & Industrial Engineering 2012, 62, 927 -935.
AMA StyleNuno Costa, Joao Lourenco, Zulema Lopes Pereira. Responses modeling and optimization criteria impact on the optimization of multiple quality characteristics. Computers & Industrial Engineering. 2012; 62 (4):927-935.
Chicago/Turabian StyleNuno Costa; Joao Lourenco; Zulema Lopes Pereira. 2012. "Responses modeling and optimization criteria impact on the optimization of multiple quality characteristics." Computers & Industrial Engineering 62, no. 4: 927-935.
Small bias and high robustness at optimal variable settings are desirable properties to all the responses involved in a multiresponse optimization problem. An approach that considers those properties and can be easily used by practitioners is presented. Its feasibility is illustrated using two examples from the literature and the results compared with those of other effective methods.
Nuno Costa; João Lourenço; Zulema Lopes Pereira. OPTIMIZATION OF THE MEAN AND STANDARD DEVIATION OF MULTIPLE RESPONSES. Iaeng Transactions on Engineering Technologies Volume 7 2012, 216 -229.
AMA StyleNuno Costa, João Lourenço, Zulema Lopes Pereira. OPTIMIZATION OF THE MEAN AND STANDARD DEVIATION OF MULTIPLE RESPONSES. Iaeng Transactions on Engineering Technologies Volume 7. 2012; ():216-229.
Chicago/Turabian StyleNuno Costa; João Lourenço; Zulema Lopes Pereira. 2012. "OPTIMIZATION OF THE MEAN AND STANDARD DEVIATION OF MULTIPLE RESPONSES." Iaeng Transactions on Engineering Technologies Volume 7 , no. : 216-229.
Nuno Ricardo Costa; Joao Lourenco; Zulema Lopes Pereira. Multiresponse Optimization and Pareto Frontiers. Quality and Reliability Engineering International 2011, 28, 701 -712.
AMA StyleNuno Ricardo Costa, Joao Lourenco, Zulema Lopes Pereira. Multiresponse Optimization and Pareto Frontiers. Quality and Reliability Engineering International. 2011; 28 (7):701-712.
Chicago/Turabian StyleNuno Ricardo Costa; Joao Lourenco; Zulema Lopes Pereira. 2011. "Multiresponse Optimization and Pareto Frontiers." Quality and Reliability Engineering International 28, no. 7: 701-712.
Nuno Costa; João Lourenço; Zulema L. Pereira. Desirability function approach: A review and performance evaluation in adverse conditions. Chemometrics and Intelligent Laboratory Systems 2011, 107, 234 -244.
AMA StyleNuno Costa, João Lourenço, Zulema L. Pereira. Desirability function approach: A review and performance evaluation in adverse conditions. Chemometrics and Intelligent Laboratory Systems. 2011; 107 (2):234-244.
Chicago/Turabian StyleNuno Costa; João Lourenço; Zulema L. Pereira. 2011. "Desirability function approach: A review and performance evaluation in adverse conditions." Chemometrics and Intelligent Laboratory Systems 107, no. 2: 234-244.
Optimization measures for evaluating compromise solutions in multiresponse problems formulated in the Response Surface Methodology framework are proposed. The measures take into account the desired properties of responses at optimal variable settings, namely, the bias, quality of predictions and robustness, which allow the analyst to achieve compromise solutions of interest and feasible in practice, namely in the case of a method that does not consider in the objective function the responses’ variance level and correlation information is used. Two examples from the literature show the utility of the proposed measures.
Nuno Costa; Zulema Lopes Pereira; Martín Tanco. Assessing Response’s Bias, Quality of Predictions, and Robustness in Multiresponse Problems. Lecture Notes in Electrical Engineering 2011, 445 -457.
AMA StyleNuno Costa, Zulema Lopes Pereira, Martín Tanco. Assessing Response’s Bias, Quality of Predictions, and Robustness in Multiresponse Problems. Lecture Notes in Electrical Engineering. 2011; ():445-457.
Chicago/Turabian StyleNuno Costa; Zulema Lopes Pereira; Martín Tanco. 2011. "Assessing Response’s Bias, Quality of Predictions, and Robustness in Multiresponse Problems." Lecture Notes in Electrical Engineering , no. : 445-457.
Checking whether process and product are satisfying or functioning according to the technical specification is not enough to assure competitiveness. Competition compels organizations to develop efforts to assure that product and process characteristics are on target values and the variability around those targets is minimal. This article proposes an alternative method for optimizing both the mean and standard deviation of a quality characteristic of the process or product. The objective function accommodates all the response types, allowing the practitioner to assign distinct weights to process mean and standard deviation and to find trade-off solutions between them, taking their relative magnitudes into account. Two classical examples from the literature are used to illustrate the feasibility of the proposed method and compare its results with those of other popular methods. A practical procedure for implementing the proposed method is also presented.
Nuno Ricardo Pais Costa. Simultaneous Optimization of Mean and Standard Deviation. Quality Engineering 2010, 22, 140 -149.
AMA StyleNuno Ricardo Pais Costa. Simultaneous Optimization of Mean and Standard Deviation. Quality Engineering. 2010; 22 (3):140-149.
Chicago/Turabian StyleNuno Ricardo Pais Costa. 2010. "Simultaneous Optimization of Mean and Standard Deviation." Quality Engineering 22, no. 3: 140-149.