Condition Monitoring to Enable Predictive Maintenance on a Six-Die Nut Manufacturing Machine through Force Data Analysis

Nut fasteners are produced by machines working around the clock. Companies generally operate with a run-to-failure or planned maintenance approach. Even with a planned maintenance schedule, however, undetected damage to the dies and non-die parts occurring between maintenance periods can cause considerable downtime and pervasive damage to the machine. To address this shortcoming, force data from the fourth and sixth dies of a six-die nut manufacturing machine were analysed using correlation to the best health condition on the force profile and on the force shock response spectrum profile. Fault features such as quality adjustments and damage to both die and non-die parts were detectable prior to required maintenance or machine failure. This detection was facilitated by the determination of health thresholds, whereby the force SRS profile generated a longer warning period prior to failure. The analytical approach could benefit the industry by identifying damage that would normally go undetected by operators, thereby reducing downtime, extending die life, enabling “as needed” maintenance, and optimising machine operation.

Micromechanics of Drilling: A Laboratory Investigation of Formation Evaluation at the Bit

Challenging drilling applications and low oil prices have created a new emphasis on innovation in the industry. This research investigates the value of drill bit based force sensing at the rock-cutter interface. For this purpose, a laboratory-based mini-rig has been built in order to recreate a scaled drilling process. The work aims to build a better understanding of the collected force and torque data despite the semi-continuous drilling process. This data is then used to estimate the formation strength. A scaled drill bit with two cutters was designed with sensors integrated into the drill bit cutter, drill string and the mini-rig structure. The mini-rig design allowed the accurate control of depth of cut by utilizing a comprehensive data acquisition and control system during the experiments. Initially, fifty-five samples were prepared with various water/gypsum ratios for a uniaxial compression test, scratch test, and for testing in the mini-rig. Prior to the mini-rig experiments, the results of the uniaxial compression and scratch tests were used as a benchmark to extract rock properties and the state of stress behavior. The experiments under atmospheric conditions revealed that the mini-rig could accurately estimate formation strength from a few rotations. The force data at the bit-rock interface was correlated with the torque measurements, and the results indicate that the tangential force has similar trends and relatively similar values. The groove created by the drill bit's rotating trajectory has a 14.45 cm circumference. This allows for a significant amount of data to be captured from a single rotation. The circular cutter geometry's influence is crucial for a continuous process since the active cutting area is continuously changing due to the pre-cut groove. The performed depth of cuts ranged from 0.1 to 1 mm in the same groove, and thus the active cutting area can be accurately calculated in real-time while conducting the experiments. Tangential and normal force data from the scratch test was analyzed in order to provide insights for correlation with the mini-rig data. The analysis shows that both tests give similar trends to the force measurements from the mini-rig. Moreover, the benchmark value of formation strength that was obtained from the uniaxial compression test was also in the same range. This illustrates the potential viability of drill bit based formation strength measurement due to the similarity between mini-rig test results and those using more classical testing practices. The experimental setup can provide a continuous cutting process that allows an accurate estimation of formation strength during a semi-continuous drilling operation with analogous application in the field. This can lead to an in-depth understanding of drilled formation properties while drilling and possibly assist in evaluating cutter wear state in-situ.

Measurement push and pull forces on automatic liquid dispensers

<span lang="EN-US">Since the COVID-19 pandemic, automated liquid dispensers have been increasingly developed to assist transmission prevention. However, data availability of automatic liquid dispenser mechanism's technical characteristics is not yet widely available. This causes frequent over or under design in its development. Therefore, we specifically measure push and pull forces engineering characteristics generated by the automatic liquid dispenser mechanism. A wire mechanism-based automatic liquid dispenser apparatus was used to experiment. A load-cell sensor was used to detect the force that occurs from a servo motor controlled by a microcontroller. The force data (push and pull) will be sent directly to the database server cloud with a recording </span><span lang="EN-US">frequency of every second. Three types of fluid treatment levels are used i.e. water, liquid soap, and hand sanitizer gel. Three types of fluid volume treatment levels used were 50 ml, 150 ml, and 250 ml. Each treatment level combination is carried out at the servo motors rotation steps 180</span><span lang="EN-US">°</span><span lang="EN-US">, 150</span><span lang="EN-US">°</span><span lang="EN-US">, 120</span><span lang="EN-US">°</span><span lang="EN-US">, 90</span><span lang="EN-US">°</span><span lang="EN-US">, 60</span><span lang="EN-US">°</span><span lang="EN-US">, and 30</span><span lang="EN-US">°</span><span lang="EN-US">. The results show that no significant differences were found in maximal forces required to release the water, liquid soap, and hand-sanitizer gel. It is also known that the volume of the fluid has a very significant effect on the amount of push and pull forces generated.</span>

Comparative Study of Popular Deep Learning Models for Machining Roughness Classification Using Sound and Force Signals

This study compared popular Deep Learning (DL) architectures to classify machining surface roughness using sound and force data. The DL architectures considered in this study include Multi-Layer Perceptron (MLP), Convolution Neural Network (CNN), Long Short-Term Memory (LSTM), and transformer. The classification was performed on the sound and force data generated during machining aluminum sheets for different levels of spindle speed, feed rate, depth of cut, and end-mill diameter, and it was trained on 30 s machining data (10–40 s) of the machining experiments. Since a raw audio waveform is seldom used in DL models, Mel-Spectrogram and Mel Frequency Cepstral Coefficients (MFCCs) audio feature extraction techniques were used in the DL models. The results of DL models were compared for the training–validation accuracy, training epochs, and training parameters of each model. Although the roughness classification by all the DL models was satisfactory (except for CNN with Mel-Spectrogram), the transformer-based modes had the highest training (>96%) and validation accuracies (≈90%). The CNN model with Mel-Spectrogram exhibited the worst training and inference accuracy, which is influenced by limited training data. Confusion matrices were plotted to observe the classification accuracy visually. The confusion matrices showed that the transformer model trained on Mel-Spectrogram and the transformer model trained on MFCCs correctly predicted 366 (or 91.5%) and 371 (or 92.7%) out of 400 test samples. This study also highlights the suitability and superiority of the transformer model for time series sound and force data and over other DL models.

Gender and Work in South Africa

This chapter provides an overview of women’s participation in the post-apartheid South African economy. It documents rising labour-force participation among women, as well as an increase in the share of total and high-skilled employment held by women. However, it also highlights some of the persistent challenges, among them that women’s labour-force participation, access to (high-skilled) employment, and earnings remain well below men’s using the most recent labour force data available. A key constraint to women’s success in the labour market is the additional responsibility they face in the home. The chapter uses data from various sources to show that women retain primary responsibility for the household and the provision of care in South Africa. Finally, attention is drawn to how the Covid-19 crisis has not only exposed the value of this unpaid labour to society, but also the difficulty of performing this work alongside the demands of paid work.

A Simple Brushless Motor and Propeller Test Stand for Experiment from Home

A brushless motor and propeller test stand is used to test brushless motors and propellers. This testing instrument is still only available in research laboratories. Students and researchers are unable to use laboratory facilities because of the Covid-19 epidemic, thus students must be able to do tests independently from home. Purchasing this testing instrument would be too expensive for students. It is essential to construct a brushless motor and propeller testing instrument at home using simple components that are easy to get on the marketplace. The design concept reads force data using a loadcell sensor and an HX711 driver, and current and voltage data with an INA 219 sensor. The brushless motor’s rotational speed is controlled by a potentiometer. Force, current, voltage, and power are all examples of test results data. A 16×2 LCD is used to show data immediately. Data is also transmitted via a USB connection to a computer device for storage or additional analysis. This study proposes a simple brushless motor and propeller test stand that can measure forces from 0 gf to 1000 gf with an error rate of 0.72 %. The power that can be read ranges from 0 mW to 18960 mW, with a 0.59 % error rate.

The Ties That Bind: Camaraderie in Military Interprofessional Healthcare Teams

ABSTRACT Introduction Multiple aspects of interpersonal dynamics can help or hinder the success of teams, particularly those in a Military Interprofessional Healthcare Team (MIHT). One specific mechanism for MIHTs’ success is camaraderie and how these military teams are able to achieve, maintain, and enable the development of this important characteristic. Despite our understanding of military service members as being bonded like a family, we have a limited understanding of how this bond is translated into their MIHT experiences. Materials and Methods This study conducted interviews among 30 individuals who had participated in, led individual, and/or led many MIHTs, using a grounded theory methodology. Participants represented 11 different health professions, including officers and enlisted military members, and three branches of the U.S. military (e.g., army, navy, and air force). Data were collected and analyzed in iterative cycles until saturation was achieved. Results We identified six themes that shaped the overarching concept of camaraderie in MIHTs. These themes were (1) confidence in competent peers, (2) shared goals, (3) mutual respect, (4) desire to help one another improve, (5) personal is professional, and (6) bonds of military service. This paper describes each of these themes, provides illustrative examples from the data, and describes how these components contribute to MIHTs’ team dynamics. We present a model for how to understand these themes. Conclusions Through the identification and exploration of these aspects of camaraderie, we are able to better understand how MIHTs are able to be successful. MIHTs that demonstrated confidence in their brother/sister in arms possessed shared goals and missions, while maintaining mutual respect, a desire to help one another do better, and creating a personal and professional overlap tended to form stronger bonds of military service. Critically, these six aspects support a more nuanced understanding of the spirit of camaraderie and how it underpins MIHT success.

Perseverance: An Essential Trait of Military Interprofessional Healthcare Teams

ABSTRACT Introduction Perseverance—doing something despite difficulty—is an asset to healthcare professionals, yet not all providers display this trait. The literature offers no conceptualization of perseverance as it relates to military caregivers. This research sought to explore the perseverance displayed by members of military interprofessional healthcare teams (MIHTs) and to construct a framework for explaining the role of perseverance in MIHTs’ collaborative work. Methods Using Grounded Theory, this interview-based study collected insights from 30 individuals who had participated in MIHTs and/or led MIHTs. Participants represented 11 different health professions, both officers and enlisted military members, and three branches of the U.S. military (i.e., Army, Navy, and Air Force). Data were collected and analyzed in iterative cycles until theme saturation was achieved. Results We identified practices through which perseverance was exhibited by members of MIHTs: (1) humility, (2) mission focus, (3) team effort, (4) failure is not an option, (5) comfort with discomfort, and (6) continuous improvement. We then clustered these practices into three subcategories, reflecting how certain practices may connect to support MIHT perseverance. Conclusions These six practices appear connected in significant ways to support the MIHTs’ efforts. Humility, mission focus, and team effort can help team members collaborate as a unified and mutually supportive team. From this base, MIHTs seemed able to become comfortable with discomfort and to refuse failure as an option. These orientations then allowed the team to engage in continuous improvement. Together, these practices may enhance team perseverance and ultimately team performance.