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Surface roughness has been proved to be influencing the running-in wear of machined components under dry and lubricated sliding conditions. Zinc dialkyl dithiophosphate (ZDDP) is widely used as an anti-wear additive, which reduces the wear by the formation of a tribofilm on the surface (Spikes, 2004). Factors such as temperature, sliding distance, etc. influence the formation of the film. A significant reduction in the power loss due to friction and wear is possible if a synergy is attained between surface roughness effects and the effectiveness of the tribofilm. The present work aims to study the influence of surface roughness and ZDDP addition on the formation and removal of the tribofilm under high contact pressures.

Samples were prepared by machining. Surface roughness was varied by varying the milling parameters. A reciprocating friction and wear test machine with a ball-on-flat geometry was used for the study. Tests were performed with mineral base oil and base oil added with 1 per cent by weight ZDDP under different operating parameters. Atomic force microscopy (AFM) and scanning electron microscopy (SEM) with energy dispersive X-Ray spectroscopy (EDS) analysis were conducted to study the surface morphology of the tribofilm.

A quasi-steady-state analysis conducted showed that the wear rate was much lower when tested with base oil containing ZDDP after about 65 min. AFM analysis confirmed the presence of chemically reacted films on the surface. SEM analysis revealed agglomeration of crystal like glassy phosphates. However, high contact pressures at the interface caused the removal of the films resulting in variations in the coefficient of friction. A comparison of the wear rates among the samples of different roughness values tested at 100°C showed that the anti-wear performance of ZDDP was not effective due to high contact pressures.

The findings in this study regarding the tribofilm formation with ZDDP additive and its failure due to high contact pressures will be beneficial for further investigation on wear resistant boundary films developed under such extreme conditions.

This study aims to simulate the influence of surface texturing produced via turning process toward pressure distribution and load capacity generation using computational fluid dynamics (CFD).

The dimple geometry was obtained via turning process, to be used for future application on piston skirt surfaces. Two cases were studied: a preliminary study using single periodic dimple assuming linear dimple distribution and an application study using multiple periodic dimples to address actual dimple orientation following the turning process.

For the first case, the dimple was proven to generate load capacity with regard to untextured surface, owing to the asymmetric pressure distribution. Increasing the Reynolds number, dimple width and dimple depth was found to increase load capacity. For the second case, although load capacity increases via surface texturing, the value was 97.4 per cent lower relative to the first case. This confirmed the importance of doing multiple dimple simulations for real applications to achieve more realistic and accurate results.

A new concept of dimple fabrication using a low-cost turning process has been developed, with a potential to increase the tribological performance under hydrodynamic lubrication. Previous CFD simulations to simulate these benefits have been done using a single periodic dimple, assuming equal distribution array between dimples. However, due to the different orientations present for dimples produced using turning process, a single periodic dimple simulation may not be accurate, and instead, multiple dimple simulation is required. Therefore, present research was conducted to compare the results between these two cases and to ensure the accuracy of CFD simulation for this type of dimple.

Equipment performance helps the manufacturing sector achieve operational and financial improvements despite process variations. However, the literature lacks a clear index or metric to quantify the monetary advantages of enhanced equipment performance. Thus, the paper presents two innovative monetary performance measures to estimate the financial advantages of enhancing equipment performance by isolating the effect of manufacturing fluctuations such as product mix price, direct and indirect characteristics, and cost changes.

The research provides two measures, ISB (Improvement Saving Benefits) and IEB (Improvement Earning Benefits), to assess equipment performance improvements. The effectiveness of the metrics is validated through a three stages approach, namely (1) experts' binary opinion, (2) sample, and (3) actual cases. The relevant data may be collected through accounting systems, purpose-built software, or electronic spreadsheets.

The findings suggest that both measures provide an effective cost–benefit analysis of equipment performance enhancement. The measure ISB indicates savings from performance increases when equipment capacity is greater than product demand. IEB is utilised when equipment capacity is less than product demand. Both measurements may replace the unitary cost variation, which is subject to manufacturing changes.

Manufacturing businesses may utilise the ISB and IEB metrics to conduct a systematic analysis of equipment performance and to appreciate the financial savings perspective in order to emphasise profitability in the short and long term.

The study introduces two novel financial equipment performance improvement indicators that distinguish the effects of manufacturing variations. Manufacturing variations cause cost advantages from operational improvements to be misrepresented. There is currently no approach for manufacturing organisations to calculate the financial advantages of enhancing equipment performance while isolating production irregularities.

The impact of digitalisation on smaller firms remains sparsely studied across emerging economies. The paper aims to examine the relationship between digital adoption and multiple performance parameters of micro, small and medium enterprises (MSME) in a prominent emerging economy.

The study employs data from the World Bank Enterprise Survey (WBES) 2022, capturing 9,024 Indian MSME firms spread across the country. Performance indicators are derived from growth in sales, employment and labour productivity (LPROD). Multiple regression estimates are derived that also correct for sample selection bias using Heckman’s two-step process.

Digital proliferation is found to increase as firms mature up in terms of age, size and constitution. A significant difference could also be observed in business performance across digital and non-digital businesses, with sales growth (SG) and productivity higher for digital firms. Digital financial variables are found to have a significant impact on SG but not as much in the case of employment growth and LPROD. The results are robust to correction for sample selection bias in digital adoption using inverse mills ratio (IMR).

The study highlights digital adoption gaps across various strata of MSMEs, highlighting lower adoption when firms are younger, smaller and lacking formal constitutional setup. Digital variables indicating positive association with SG highlight the need for concerted efforts at the public policy level for building appropriate skills and infrastructure for micro and small enterprises to boost their digital adoption to promote growth.

There is a lack of micro-level empirical evidence measuring the impact of advanced digital technology usage on multiple aspects of enterprise performance amongst micro and small firms. The study deploys unique digital variables including TReDS and use of online credit applications to assess the impact on business performance. The findings provide insights for practice and public policy, besides making the case for a higher focus on launching digital initiatives for smaller enterprises.

The paper aims to develop an efficient and compact hybrid S-curve-PSO (particle swarm optimization) controller for the optimal trajectory planning of industrial robots in the presence of obstacles, especially those used in pick-and-place operations.

The proposed methodology comprises a monotonic trajectory through bounded entropy of speed, velocity, acceleration and jerk. Thus, the robot’s trajectory planning corresponds with S-curve-PSO duality. This is achieved by dual navigation with minimal computational complexity. The matrix algebra-based computational complexity transforms the trajectory from random to compact. The linear programming problem represents the proposed robot in Euclidean space, and its optimal solution sets the corresponding optimal trajectory.

The proposed work ensures the efficient trajectory planning of the industrial robot in the presence of obstacles with optimized path length and time. The real-time and simulation analysis of the robot is presented for performance measurement, and their outcomes demonstrate a good correlation. Compared with the existing controller, it gives a noteworthy improvement in performance.

The novel S-curve-PSO hybrid approach is presented here, along with the LIDAR sensors, which generate the environment map and detect obstacles for autonomous trajectory planning. Based on the sensory information, the proposed approach generates the optimal trajectory by avoiding obstacles and minimizing the travel time, jerk, velocity and acceleration. The hybrid S-curve-PSO approach for optimal trajectory planning of the industrial robot in the presence of obstacles has not been presented by any researchers. This method considers the robot’s kinematics as well as its dynamics. The implementation of the PSO makes it computationally superior and faster. The selection of best-fit parameters by PSO assures the optimized trajectory in the presence of obstacles and uncertainty.

Aims to evaluate the effectiveness of 2‐amino 4‐phenyl thiazde (APT) and its three anils as inhibitors for the corrosion of mild steel in 1M HCl. Discusses the variation of inhibition efficiency with temperature. Gives account of experimental procedures on mild steel strips for weight loss measurements and potentiodynamic polarization studies.

The purpose of this paper is to examine the development of rice supply chain in the context of the role of rice farmer organizations and cooperative networks in Thailand.

Primary data were solicited from the cooperatives and members of cooperatives for this study through questionnaire administration. The questionnaire containing a five-point Likert scale was posed to respondents to ascertain their problems before and after joining the network (for cooperative) and after joining the cooperative (for members). This study employed the independent two-sample student t-test (two-tailed) to test for significant difference in the means of scores regarding the problems of cooperatives before and after the cooperative network, and also to test for significant difference in the means of scores of the problems of members of the cooperatives before and after joining the cooperative.

The study revealed that key production and marketing problems such as increased transaction costs and market uncertainties confronting the cooperative organizations have been diminished as a result of the networks. Key problems of the members of the cooperatives such as exploitation and opportunistic behavior of traders to whom they sell their products have been reduced as a result of joining the cooperatives.

This paper is not without caveat. The governance structures in relation to leadership, financial arrangements and bargaining power balance have not been analyzed in this study and these are avenues for further research.

To the best of the authors’ knowledge, this study is the first that examined the combined roles of farmer organizations and cooperative networks in developing the rice supply chain in Thailand.

The purpose of this paper is to examine the relative influence of “reasons for” and “reasons against” adoption of mobile banking (m-banking) among Indian consumers.

Using the framework of behavioral reasoning theory (BRT), hypothesized relationships between values, reasoning constructs, attitude and intentions were developed. The hypotheses were tested using a representative sample of data obtained from Indian banking consumers (n=379). Confirmatory factor analysis and structural equation modeling were used to analyze the data.

The findings indicate that both “reasons for” and “reasons against” have an influence on m-banking adoption. Among the “reasons for” m-banking adoption, ubiquitous is the major determinant, and among the “reasons against” m-banking adoption, tradition barrier is the major determinant. The findings also confirm that value of “openness to change” significantly influences reasons for adoption and has no impact on reasons against and attitude toward m-banking.

This study examines customers in only one context (i.e. India). Future research can examine samples in other countries so that the results can be generalized. Also the mediating role of demographic factors can be studied in future studies to predict m-banking adoption.

The findings of this study emphasize the importance of examining both the pro-adoption and anti-adoption factors while developing marketing strategy. This study confirms that m-banking adoption can be increased if managers attempt to minimize the effect of barriers of m-banking adoption.

This is the first study to examine m-banking adoption using BRT, which investigates the reasons for and reasons against m-banking adoption in a single framework.