Nuno Ricardo Costa

Multiple response optimization: a global criterion‐based method

Processes and products have by nature many quality characteristics that must be in some sense optimized simultaneously. With this aim, a method which can be used easily and efficiently by practitioners for optimizing multi‐response problems is proposed. Implementation steps and considerations, in addition to optimization measures to assess methods solutions and guide the analyst in finding an effective compromise solution, are also presented. Three classical examples from the literature are used to assess the performance of several prominent methods in the response surface methodology (RSM) framework and help practitioners make a better‐informed choice among them. Copyright

Guidelines to help practitioners of design of experiments

Purpose – The purpose of this paper is to focus the application of design of experiments (DOE) using industrial equipments, reinforcing idea that non‐statistical aspects in planning and conducting experiments are so important as formal design and analysis.Design/methodology/approach – Two case studies are presented to illustrate typical industrial applications and difficulties. Supported on these case studies and literature, this paper presents guidelines to planning, conducting and analysis involving technical and organizational aspects.Findings – Solving problems in industry, including in companies recognized as competent in the respective industrial sector, is not just a question of applying the right technique. Ceramic industry case study illustrates how important are non‐statistical issues in DOE application. Paint industry case study illustrates the strong relationship of the results with incorporating presented guidelines into practice. Moreover, both case studies consolidating a fundamental advant...

Gaussian Process Model – An Exploratory Study in the Response Surface Methodology

This paper explores the benefits of Gaussian process model as an alternative modeling technique for problems developed in the Response Surface Methodology framework. Three case studies with different type and number of responses were investigated, and the compromise solutions obtained with three modeling techniques were evaluated. Results provide evidences of the Gaussian process model usefulness for stochastic responses, namely, when responses are correlated. Copyright

Multiresponse problems: desirability and other optimization approaches

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.

Real-time app development approach for indoor monitoring

After a contextualization of mobile applications, this paper presents a approach for real-time mobile application development. Through the presented approach it is proposed to use different hardware components and technologies accessible in mobile devices, namely WIFI, GSM, sensors as well as colored Petri nets for modeling the behavior of the system.

Exploring Pareto Frontiers in the Response Surface Methodology

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.

Simulation of real–life situations in multiresponse problems: a contribution to criteria evaluation in the RSM framework

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.

On the selection of significant variables from unreplicated factorial designs

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.