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The main objective of this paper is to report the development of an indirect force control strategy designed to operate with industrial robotic deburring applications. More specifically, the system reported here is developed to debur high‐quality knives that incorporate innovative design from well‐known authors (fashion designers). Therefore, these products are very difficult to manufacture and have quality requirements incompatible with human‐based deburring, since humans introduce too many unacceptable deviations as a consequence of their incapacity to maintain concentration for long periods of time.

Since a good model of the environment is difficult to obtain, namely on industrial applications, a simple strategy was designed to obtain the relevant parameters leading to an acceptable performance. Consequently, the system implements an indirect force control strategy as a way to use actual robot controllers, explore the computing power of external personal computers, and the advanced features of modern force‐torque sensors. The proposed strategy is presented in some detail and further discussed using a few test‐case experiments.

Experiments show a usable setup for contour following which is very useful to obtain the work‐piece profile. A good selection of the path step seems to be, as expected, one of the most important variables to achieve good results: the smaller the increment over the trajectory the more regular is the resulting force profile. Low speeds also seem to lead to better results. The strategy implemented to maintain contact with the object and keep contact force at a certain level seems to result over surfaces with a smooth and large radius continuity, although there are significant force variations on impact with objects (which is not important since impacts can be planned), especially at the higher speeds, and even more significant near object edges. The desired contact force is also a parameter that should be tested. In the presented experiments, a contact force of 10 N was selected and oscillations of 1 N were observed around this value. In an industrial environment, more exposed to noise and vibrations, a higher contact force may be required. On the other hand, the increase of the contact force also increases the flexion of the sensing tool what brings more uncertainty to the calculated contact point. Large force oscillations imply more uncertainty of the obtained work‐piece contour. Like in any industrial process selected parameters are the ones that show acceptable results at higher execution speeds.

The objective of the presented setup is to find the better compromise for a particular industrial application, achieving acceptable operational cycle times.

The obtained results are encouraging and the ability to perform contour recognition under a specified contact force can be very useful with the automatic deburring system being developed. In fact, this feature enables the system to acquire the exact contour of the working piece in the exact same conditions that will be used for the subsequent deburring task. This will contribute to minimize error and increase the process speed.

This paper presents Quick Changeover Design (QCD), which is a structured methodological approach for Original Equipment Manufacturers to drive and support the design of machines in terms of rapid changeover capability.

To improve the performance in terms of set up time, QCD addresses machine design from a single-minute digit exchange of die (SMED). Although conceived to aid the design of completely new machines, QCD can be adapted to support for simple design upgrades on pre-existing machines. The QCD is structured in three consecutive steps, each supported by specific tools and analysis forms to facilitate and better structure the designers' activities.

QCD helps equipment manufacturers to understand the current and future needs of the manufacturers' customers to: (1) anticipate the requirements for new and different set-up process; (2) prioritize the possible technical solutions; (3) build machines and equipment that are easy and fast to set-up under variable contexts. When applied to a production system consisting of machines subject to frequent or time-consuming set-up processes, QCD enhances both responsiveness to external market demands and internal control of factory operations.

The QCD approach is a support system for the development of completely new machines and is also particularly effective in upgrading existing ones. QCD's practical application is demonstrated using a case study concerning a vertical spindle machine.

Since sovereign ratings provided by credit rating agencies (CRAs) are a key determinant of the interest rates a country faces in the international financial market and once sovereign ratings may have a constraining impact on the ratings assigned to domestic banks or companies, some studies have focused on identifying the determinants of sovereign credit risk assessments provided by CRAs. In particular, this study estimates the effect of fiscal credibility on sovereign risk using four different comprehensive credit rating (CCR) measures obtained from CRAs' announcements and two different fiscal credibility indicators.

We build comprehensive credit rating (CCR) measures to capture sovereign risk. These measures are calculated using sovereign ratings, the rating outlooks and credit watches issued by the three main credit rating agencies (S&P, Moody's and Fitch) for long-term foreign-currency Brazilian bonds. Based on monthly data from 2003 to 2018, we use different econometric estimation techniques in order to provide robust results.

The results indicate that fiscal credibility exerts both short- and long-run effects on sovereign risk perception, and macroeconomic fundamentals are important long-run determinants.

Since fiscal credibility reflects the government's ability to maintain budgetary balance and sustainable public debt, the government should keep its commitment to responsible fiscal policies so as not to deteriorate expectations formed by financial market experts about the fiscal scenario and, thus, to achieve better credit assessments issued by CRAs with respect to sovereign debt bonds. Sovereign credit rating assessment is a voluntary practice. It is up to the country whether they want to apply for a rating assessment or not. Thus, without a sovereign rating, one must find an alternative to measure the sovereign risk of a country. In this sense, an important practical implication that this study provides is that fiscal credibility can be used as a leading indicator of sovereign risk perceptions obtained from CRAs or even as a proxy for sovereign risk.

This paper is the first to verify how important the expectations of financial market experts in relation to the fiscal effort required to keep public debt at a sustainable level (i.e. fiscal credibility) are to sovereign risk perception of credit rating agencies. In this sense, the study is the first to address this relation, and thus it contributes to the literature that seeks to understand the determinants of sovereign ratings in emerging countries.

Employment mismatch is a significant problem in many countries. However, little conceptualization research has been conducted on employment mismatch from a social justice perspective. The purpose of this study is to shed light on social justice issues that have been obscured in the human resource development (HRD) literature through the lens of the distributive justice theory.

This study first reviews the literature to identify the gaps in employment mismatch research by reviewing three relevant bodies of literature: education mismatch, immigrant mismatch and disability mismatch. It then provides a new conceptualization of employment mismatch by examining employment mismatch through the lens of Rawls’ (1971) distributive justice theory.

The author proposed a framework of healthy employment relations using the constructs of social system design, moral guidance, education reform and individual development. Implications were proposed for research and practice.

The new framework of healthy employment approaches employment mismatch from four aspects embraced by the distributive justice theory. This model can assist HRD professionals and policymakers in responding to the employment mismatch of different populations.

Given the importance of credit rating agencies’ (CRAs) assessment in affecting international financial markets, it is useful for policymakers and investors to be able to forecast it properly. Therefore, this study aims to forecast sovereign risk perception of the main agencies related to Brazilian bonds through the application of different machine learning (ML) techniques and evaluate their predictive accuracy in order to find out which one is best for this task.

Based on monthly data from January 1996 to November 2018, we perform different forecast analyses using the K-Nearest Neighbors, the Gradient Boosted Random Trees and the Multilayer Perceptron methods.

The results of this study suggest the Multilayer Perceptron technique is the most reliable one. Its predictive accuracy is relatively high if compared to the other two methods. Its forecast errors are the lowest in both the out-of-sample and in-sample forecasts’ exercises. These results hold if we consider the CRAs classification structure as linear or logarithmic. Moreover, its forecast errors are not statistically associated with periods of changes in CRAs’ opinion of any sort.

To the best of the authors’ knowledge, this study is the first to evaluate the performance of ML methods in the task of predicting sovereign credit news, including not only the sovereign ratings but also the outlook and credit watch status. In addition, the authors investigate whether the forecasts errors are statistically associated with periods of changes in sovereign risk perception.

This study reexamines the sustainability of fiscal policy in Sweden.

To test the sustainability of fiscal policy, two approaches are used; the methodology of Kejriwal and Perron (2010), testing for multiple structural changes in a cointegrated regression model and time-varying cointegration test of Bierens and Martins (2010), and Martins (2015).

Using the first approach of testing for multiple structural changes in a cointegrated regression model, the results indicate that government spending and revenue are cointegrated with two breaks. An estimation of a two-break long-run model shows that the slope coefficient increases from 0.678 to 0.892 from the first to the second regime, implying that fiscal deficits were weakly sustainable in the first two regimes, from 1800 to 1943, and from 1944 to 1974. Further, results from time-varying cointegration test indicate that cointegration between spending and revenue in Sweden is time-varying. Fiscal deficits were found to be unsustainable for the periods 1801–1811, 1831–1838, 1853–1860 , 1872–1882, 1897–1902, 1929–1940 and 1976–1982 and weakly sustainable over the rest of the study period.

A number of implications arise from this study: (1) Accounting for breaks in cointegration analysis and in the estimation of the level relationship between spending and revenue is very important because ignoring breaks may lead to an overestimated slope coefficient and hence a bias on the magnitude of fiscal deficit sustainability. (2) In testing for cointegration between spending and revenue, assuming a constant cointegrating slope when it is actually time-varying can also be misleading because deficits can be sustainable for a period of time and unsustainable over another period.

The contribution of this study is three-fold; first, the study uses a long series of annual data spanning over a period of two centuries, from 1800 to 2011. Second, because of the importance of structural change in economics, to examine the existence of a level relationship between spending and revenue, the study uses the methodology of Kejriwal and Perron (2010) to test for multiple structural changes in a cointegrated regression model, as well as time-varying cointegration of Bierens and Martins (2010) and Martins (2015).

The objective of this research is to develop an solution to water management at the scale of buildings, through the technological resources. Automating analysis using 3D models helps increase efficiency in buildings during the operational phase, consequently promotes sustainability.

This study presents a methodology based on Design Science Research to automate water management at building scale integrating BIM-IoT-FM. Data from smart meters (IoT) and the BIM model were integrated to be applied in facilities management (FM) to improve performance of the building. The methodology was implemented in a prototype for the web, called AquaBIM, which captures, manages and analyzes the information.

The application of AquaBIM allowed the theoretical evaluation and practical validation of water management methodology. By BIM–IoT integration, the consumption parameters and ranges for 17 categories of activities were determined to contribute to fulfill the research gap for the commercial buildings. This criterion and other requirements are requirements met in order to obtain the AQUA-HQE environmental sustainability certification.

Traditionally, water management in buildings is based on scarce data. The practical application of digital technologies improves decision-making. Moreover, the creation of consumption indicators for commercial buildings contributes to the discussion in the field of knowledge.

This article emphasizes the investigation of the efficiency of use in commercial buildings using operational data and the use of sustainable consumption indicators to manage water consumption.

This paper examined the inclusive growth position of sub-Saharan Africa (SSA) through the metrics of poverty-gap, bottom20 and employment. Through these indicators, the study investigated the effects of domestic-investment on inclusive-growth and established the moderating impact of governance in the domestic investment-inclusive growth nexus. It further accounted for potential nonlinearity and investigated the governance threshold that moderates domestic investment-inclusive growth relationships.

Using a sample of 41-SSA countries, the paper employed the fixed effect (FE) with the Driscoll and Kraay nonparametric consistent covariance matrix estimator, the generalized method of moments (GMM) and the dynamic-panel threshold techniques.

The poverty-gap metric showed that with increasing GDP-growth, the income of the poor falls below the poverty-line, suggesting that GDP-growth episodes may have widened the poverty-gap and contributed minimally to reducing it. Findings revealed insignificant effects of GDP-growth on the bottom-20 metric while the employment-metric indicated that the “jobless-growth” phenomenon remained valid. The authors essentially established that economic growth has not been inclusive but the complementary roles played by domestic-investments and governance are essential requirements for achieving inclusive growth. The threshold-modeling indicated that countries in the upper-regime of governance gained more in reducing poverty gaps, increasing income shared by the bottom-quintile and improving employment for every percentage increase in investment. The authors confirmed nonlinearity and showed that there exists a governance threshold that respective governments in Africa must reach for domestic-investment to enhance inclusive growth.

The paper accounted for cross-sectional dependence, nonlinearity and the governance threshold needed for domestic-investment to stimulate inclusive growth.

Credit rating agencies (CRAs) are perceived as highly influential in the financial system since their announcements can affect several players in the financial markets, from big private financial and non-financial companies and their financial markets experts to sovereign states. In this sense, this study investigates whether sovereign credit news issued by CRAs (measured by comprehensive credit rating (CCR) variables) affect the uncertainties about the exchange rate in the future (captured by the disagreement about exchange rate expectations). The study is relevant once there is evidence indicating that CRAs' assessments are responsible for affecting international capital flows and, thus, sovereign rating changes can affect the expectations formation process regarding the exchange rate. In addition, there is evidence indicating that the disagreement about exchange rate expectations affects the disagreement about inflation expectations, which brings consequences to policymakers.

The dependent variables are the disagreement in expectations about the Brazilian exchange rate for different forecast horizons, 12, 24 and 36 months ahead and the first principal component of theses series. On the other hand, the CCR variables are built upon the long-term foreign-currency Brazilian bonds ratings, outlooks and credit watches provided by the main CRAs. Estimates are obtained using ordinary least squares (OLS) and generalized method of moments (GMM); a dynamic analysis is performed using vector-autoregressive (VAR) through impulse-response functions.

Negative (positive) sovereign credit news, given by a rating downgrade (upgrade) and/or a negative (positive) outlook/watch status, increase (decrease) the disagreement about exchange rate expectations. This result holds for all disagreement and CCR variables.

The study brings practical implications to both private agents (mainly financial market experts) and policymakers. An important practical implication of the study concerns the ability of CRAs to affect the expectations formation process of financial market experts regarding the future behavior of the exchange rate. When a CRA issues a signal of improvement in a country's sovereign rating, this signal reflects the perception of improvement in macroeconomic fundamentals and reduction of uncertainties about the country's ability to honor its financial obligations, which therefore, facilitates the expectations formation process, causing a reduction in the disagreement about the exchange rate expectations. With respect to the consequences for policymakers, they will have more difficulty in guiding expectations in a country with a worse sovereign risk rating, where agents have difficulties in forming expectations and the disagreement in expectations is greater.

The study is the first to analyze the impact of CRAs' announcements on the disagreement about exchange rate expectations. Moreover, it connects the literature that investigates the effects of sovereign credit news on the economy with the literature that examines the main determinants of disagreement in expectations about macroeconomic variables.

The state of Mato Grosso represents the largest producer and exporter of soybeans in Brazil; given this importance, it was aimed to propose to use the univariate imputation tool for time series, through applications of splines interpolations, in 46 of its municipalities that had missing data in the variables soybean production in thousand tons, production value and soy derivatives in R$ thousand, and also to assess the differences between the observed series and those with imputed values, in each of these municipalities, in these variables.

The proposed methodology was based on the use of the univariate imputation method through the application of cubic spline interpolation in each of the 46 municipalities, for each of the 3 variables. Then, for each municipality, the original series were compared with each observed series plus the values imputed in these variables by the Quenouille test of correlation of time series.

It was observed that, after imputation, all series were compared with those observed and are equal by the Queinouille test in the 46 municipalities analyzed, and the Wilcoxon test also showed equality for the accumulated total of the three variables involved with the production of soybeans. And there were increases of 5.92%, 3.58% and 2.84% for soy production, soy production value and soy derivatives value accumulated in the state after imputation in the 46 municipalities.

The present research and its results facilitate the process of estimates and monitoring the total soy production in the state of Mato Grosso and its municipalities from 1990 to 2018.