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The helical spring lock washer (HSLW) is a part of nut bolt joint assembly used in different industries like automobile, aerospace, mechanical, chemical, electrical, electronics, etc. It works as a part of temporary joint and plays important role in loosening behavior of assembly under dynamic (vibrations) conditions. Thus, the purpose of this paper is to investigate the performance of HSLW under different controlled operating conditions in order to satisfy its functional requirement.

In the present investigation, a novel test rig is designed and developed to determine the load-deflection characteristics of HSLWs. The test rig facilitates the controlled linear displacement of the HSLW with predetermined angular rotation of the handle gives the corresponding reaction load on the display. Additionally, the repeatability and reproducibility of the test rig was carried out.

The newly designed and developed test rig is capable enough to differentiate the load-deflection characteristics during compressive loading and unloading of HSLWs. Additionally, the loss of strain energy can be determined from the load-deflection characteristics of HSLW.

The present test rig is designed and developed to investigate the load-deflection characteristics under compressive loading and unloading of HSLW. The test rig has least count of 0.4905 N for load measurement and 0.01389 mm for linear displacement.

This paper aims to clarify the relationship between characteristics that contribute to health care access issues and individual behavior seeking health care. It proposes the different contexts of why African American and Hispanic men are not accessing health care. The study findings provided the target audience with past and present literature to contribute to the future resolution of racial and ethnic health care disparity, as well as health care access.

The paper opted for a descriptive case study using a one-on-one face-to-face semi-structured approach of a case study, including 10 depth interviews representing African American and Hispanic men who are experiencing health care access issues. The data were complemented by archival data analysis, description of personal accounts of the African American and Hispanic men and articles pertaining to racial and ethnic health disparities.

The paper provides insights into how change is brought about the improvement of health care for all races and ethnicity. It suggests that leaders act as “integrating forces” on two levels: integrating the important elements of improved health care coupled with communication, language and health care cost and mediating between the health care structures and the individual.

This paper fulfills an identified need to study the characteristics that contribute to health care access issues among African American and Hispanic men.

The purpose of this study is to address the issue of technology equipment formerly dedicated to the process of 4- and even 5-inch photovoltaic cells and whose use has become critical with the evolution of silicon wafer size standards (M2–M10). Fortunately, the recent concept of 6'' half-cut cell with its many advantages appears promising insofar as it offers the possibility of further extend the use of costly, still operational process equipment, but doomed to obsolescence.

In the background of a detailed Al-BSF process, the authors show how to experimentally adapt specific accessories and arrange 6” half-wafers to enable the upgrade of a complete industrial process of silicon solar cells at a lower cost. Step by step, the implementation of the processes for the two wafer sizes (4” wafers and 6” half wafers) is compared and analyzed in terms of performance and throughput.

Globally, the same process effectiveness is observed for both types of wafers with slightly better sheet resistance uniformity for the thermal diffusion carried out on the half wafers; however, the horizontal arrangement of the wafer carriers in the diffusion and the plasma-enhanced chemical vapor deposition tubes limits the thermal balance regarding the total number of cells processed per batch.

In terms of the development of prototypes on a preindustrial scale, this paves the way to further continue operating outdated equipment for high-performance processes (passivated emitter and rear contact, Tunnel oxide passivated contact (TOPCon)), while complying with current standards for silicon wafers up to M10 format.

The purpose of this research is to calculate and enhance the cheese cheddar manufacturing plant efficiency under actual workplace conditions by measuring reliability, availability and maintainability (RAM) indices. The authors highlight how RAM analysis is important in determining periodic maintenance and in scheduling and managing the appropriate maintenance policy.

The current work is conducted using statistical approaches to evaluate failure and repair statistics. The RAM estimation was calculated on the basis of quantitative data obtained over a span of 32 months. Descriptive statistics, Pareto analysis, as well as the presumption of independence were ensured through trend and serial correlation tests. In addition, the reliability and maintainability of the cheddar cheese processing plant and its machines were calculated at various mission periods.

The primary goal of the implementation approach is to understand the fault patterns and the accurate quantitative assessment of the reliability and maintainability of the cheddar production plant. The findings revealed the essential aspects of the line, which need improvement by an appropriate maintenance program.

This study is intended to serve to highlight the RAM assessment and its impact on the performance of the real-time system. The benefit of the technique is the continual control of the manufacturing process by means of acceptable indexes, whose use corresponds to a continuous improvement process.

The purpose of this paper is to propose an assembly robot that exhibits specific human‐like skills, with minimal structural cost and a number of external sensors.

The authors have employed vision processing using multiple cameras to determine targets and postures and propose strategies to determine the pose of a target and to prevent collisions between the fingers and obstacles in an environment with mixed objects. Furthermore, a dynamic trajectory planner integrates the vision and force sensors of the robot hand for the assigned task.

The authors obtained satisfactory experimental results for autonomous real‐time grasping and screwing. The results verified the capability of the robot for handling small objects.

More effective robotic manipulation requires a higher degree of target orientation data, which will be a future study of this research.

Practicality has been established through results, indicating the capability of the robot to implement human‐like skilled manipulation of small objects. This can potentially reduce the high labor cost associated with the small‐scale manufacture of custom‐made products.

Screwing of nuts of minimum M2 size (diameter, 4.6 mm) and M8‐M10 bolts (head diameter, 15‐19.6 mm; length, 50‐80 mm) by cooperating two seven‐link arm manipulators and three‐fingered hands shows the robot's capability to manipulate small objects.

The purpose of this paper is to develop an efficient and effective preventive maintenance (PM) plan that considers machines’ maintenance needs in addition to their reliability factor.

Similarity coefficient method in group technology (GT) philosophy is used. Machines’ reliability factor is considered to develop virtual machine cells based on their need for maintenance according to the type of failures they encounter.

Using similarity coefficient method in GT philosophy for PM planning results in grouping machines based on their common failures and maintenance needs. Using machines' reliability factor makes the plan more efficient since machines will be maintained at the same time intervals and when their maintenance is due. This helps to schedule a standard and efficient maintenance process where maintenance material, tools and labor are scheduled accordingly.

The proposed procedure will assist maintenance managers in developing an efficient and effective PM plans. These maintenance plans provide better inventory management for the maintenance materials and tools needed using the developed virtual machine cells.

This paper presents a new procedure to implement PM using the similarity coefficient method in GT. A new similarity coefficient equation that considers machines reliability is developed. Also a clustering algorithm that calculates the similarity between machine groups and form virtual machine cells is developed. A numerical example adopted from the literature is solved to demonstrate the proposed heuristic method.

Despite its envisaged benefits, integrated reporting (IR) has yet to achieve its “breakthrough”, especially among small- and medium-sized enterprises (SMEs). This study aims to discern SME leaders’ attitudes toward IR, and thereby to reveal managerial perceptions of both the potential benefits and the challenges that actually prevent them from embarking on IR.

This explorative study is grounded on semi-structured interviews with 16 managers of large German SMEs, which yet do not apply IR but are potential candidates to implement it in the future. The engagement with non-preparers is expected to paint a more representative picture of actual reasons for IR (dis-)engagement compared to prior studies that address the few firms that have adopted IR and overcome its challenges. Applying Brown and Fraser’s (2006) conceptual landscape, results are presented analogous to a business case-, stakeholder accountability- and critical theory dimension.

Contrary to prior studies, which identified stakeholder accountability endeavors as kindling SME managers’ interest in voluntary reporting initiatives, managers regard IR primarily as a business case, serving to achieve legitimacy, improve corporate image, reach out to professional investors and assist in employee recruitment. However, they refrained from actually adopting the novel reporting medium, which suggests that decision-makers might not believe the business case to be as unproblematic as claimed by the proponents of IR. This was traced back to three major impediments that currently inhibit SMEs from reporting in an integrated way, namely, a perceived lack of interest by the relevant publics, infeasibility of the IR concept to meet user needs and preparation costs. These drawbacks resemble those of earlier voluntary reporting experiments, calling into question the “revolutionary” character of IR. The study critically concludes that the future development of IR depends on addressing these barriers.

To the best of the author’s knowledge, this is the first explorative study to deliberately engage with IR non-preparers to draw conclusions on impediments to IR. The identification of relevant incentives and disincentives for IR among SME managers at first hand not only adds to the small extant IR research body and provides valuable insights for research, practice and standard setting but also contributes to the contemporary debate about dominant legitimacy-based explanations in the broader domain of social and environmental accounting and reporting.

The authors study the explanatory power of investor rationality and irrationality for value and momentum portfolios. We also examine the relationships during financial crisis events, namely, the US subprime mortgage crisis (2007–2009) and the European debt crisis (2011–2013).

This study examines the influence of investors’ rationality and irrationality on the US stock market, using the multiple linear regression model and the stepwise regression model. Technically, the stepwise regression uses the machine-learning technique, with specific testing methods — forward selection, backward selection and stepwise selection — to find the best-fit model, according to Akaike’s Information Criterion (AIC). Thus, in this study, we will show the best model, as tested by the stepwise regression model.

Our empirical results contribute to the importance of reasons and emotions for stock-market returns and conclude that rationality and irrationality simultaneously explain the value and momentum portfolios, as well as the ETF portfolios. Also, the rational and irrational explanatory powers differ, depending on portfolios and different periods. Rational factors usually explain the volatility of the return to a greater extent than irrational factors. Moreover, during a financial crisis, the irrational factors remarkably increase their importance in explaining returns, especially for the ETF portfolios.

We expect this study’s contribution will show not only academic contribution but also benefit many stakeholders in the financial market. Investors and traders can identify various irrational factors of trading — for example, taking a long position during the panic in the market following the indicators in the models. Managers also reconsider the cost of the company by adding irrational factors when computing the equity’s expected return. Similarly, stock exchanges can adequately adjust their circuit breaker during a pessimistic-investor period. Finally, regulators can evaluate a complete picture of the stock market by adding irrational factors into their considerations.

The governments of different nations implemented various policy measures in response to the COVID-19 outbreak. These policy measures had a negative impact towards freight transportation. Further, the shock and ripple effect on the other supply chain complicates the recovery process of freight transportation. The transformation of freight transportation in the post-COVID-19 world was reported to be unsustainable. Thus, emerged the requirement to formulate the recovery measures in the context of freight transportation. This study aims to identify and model the recovery measures for sustainable freight transportation (SFT).

In this study, 13 critical recovery measures are established from the literature and finalized with the help of an expert panel. An integrated Grey Decision-Making trial and evaluation laboratory is used to prioritize and establish the cause-effect relationships among the identified critical recovery measures. Further, sensitivity analysis is performed to ensure the robustness of the proposed model.

The present study reflects that Efficient traffic management (M13), sustainability focused policies (M2), sensitization of stakeholders (M10), financial support (M9) and adoption of 4 R practices (M12) are the top five critical recovery measures for SFT. The results highlight that the transport sector needs to retain the learning from the COVID-19 period to operate under low workforce availability. Further, the emerging economies are suggested to promote local manufacturing to reduce the lead time and risk of unavailability. The study findings reflect that attaining sustainability without considering the social dimension of sustainability is impossible. Also, the results shed light on the controllable and uncontrollable recovery measures.

The findings from the study would assist policymakers and practitioners in re-formulating the recovery measures for freight transportation considering the aspect of sustainability.

The resistance of the energy sector in recent time has been tried by COVID-19 as the occurrence has added to the dampening down demand for crude oil which has resulted in volatility in prices and dwindling production of crude oil at the global crude oil market. Dwindling demand and price decline can also be perceived as a trend in the electricity sector, the electricity price (ELECTP) and consumption. The consequences of individual policy response by countries in relation to the socio-economic impact of COVID-19 is yet to be known, and recent studies conducted in the continent are yet to document the impact of the pandemic on the oil-producing African countries. It is in the light of this that this study determined the effect of socio-economic shocks activated through the COVID-19 pandemic on the energy sector performance and economic development of Africa. Monthly data were sourced from the United States Energy Information Administration, COVID-19 geographic distribution worldwide, World Development Indicator and Trading Economics from 2019 (m12) to 2020 (m10). Seventeen oil-producing African countries were selected across the region based on data availability. The structural panel vector auto regression (SPVAR) analytical technique was used in estimating COVID-19 pandemic and socio-economic shocks on the energy sector performance proxied by oil production (OILP), ELECTP and economic development proxied by gross domestic product per capita (GDPPC) of the countries. Findings revealed that the COVID-19 pandemic transmits a negative shock to OILP and GDPPC while a positive shock is transmitted to ELECTP. The socio-economic variables also transmitted both the positive and negative shocks to OILP, ELECTP and GDPPC. Therefore, the study recommended that policies should be directed towards putting in place a shock-absorbing mechanism so as to cushion the effect of the identified shocks on the performance of the energy sector and the economic development of the countries.