Search results

This paper aims to overcome the inability of both comparing loss costs and accounting for production resource losses of Overall Equipment Effectiveness (OEE)-related approaches.

The authors conducted a literature review about the studies focusing on approaches combining OEE with monetary units and/or resource issues. The authors developed an approach based on Overall Equipment Cost Loss (OECL), introducing a component for the production resource consumption of a machine. A real case study about a smart multicenter three-spindle machine is used to test the applicability of the approach.

The paper proposes Resource Overall Equipment Cost Loss (ROECL), i.e. a new KPI expressed in monetary units that represents the total cost of losses (including production resource ones) caused by inefficiencies and deviations of the machine or equipment from its optimal operating status occurring over a specific time period. ROECL enables to quantify the variation of the product cost occurring when a machine or equipment changes its health status and to determine the actual product cost for a given production order. In the analysed case study, the most critical production orders showed an actual production cost about 60% higher than the minimal cost possible under the most efficient operating conditions.

The proposed approach may support both production and cost accounting managers during the identification of areas requiring attention and representing opportunities for improvement in terms of availability, performance, quality, and resource losses.

The purpose of this research is to discover equipment losses and assess the accomplishment of overall equipment effectiveness (OEE) values.

Industries specialized in die shops often have issues regarding their efficiencies, conferring to statistics further production line department procedure for various machines frequently suffered restrictions owing to excessive downtime and speed losses in machines thus, reducing their effectiveness and efficiency. OEE is a means of determining how effective a piece of equipment is when in working condition. Calculation of OEE finds the heart of the issue and the root cause for the underlying problem.

The dimensional outcomes suggest that the average machine effectiveness has not attained the norm of >85%, but there is still room for progression.

One recommended procedure to reduce losses is to keep the actual pace of operation and downtime of equipment constant. Many such suggestions are provided to reduce the losses.

China has invested massively in higher education, reaching a mass system, envisaging, as a next step, reaching a universal system. Brazil is still an elite system but needs to create adequate public policies to migrate to a mass system. The purpose of this article is to analyze the paradigms for a mass educational system, with regard to the quality of education offered, and the prospects for achieving a universal system, with Brazil and China as a reference.

The author applied an exploratory and qualitative method, through categorical content analysis. The data were collected through nine interviews with government managers, 15 unstructured (open) questionnaires to specialists in higher education and four student leadership.

The results indicate that the change from an elite system to a mass system impacts quality, as there is an inevitable change in experience. However, this modification does not testify against the mass system, as it is necessary for a nation to pass through it and structure itself adequately in order to reach the universal system, a path desired by both countries.

The study presented the reflections observed by the migration from the elite system to the mass system from the main stakeholders of the system in China and the prospects for Brazil to become a mass system. Additionally, it presented the perspectives for both countries to achieve the desired universal system.

This study aims to explore how sustainable business models (SBM) can be developed within agri-innovation systems (AIS) and emphasize an integration of the two with a systemic understanding for reducing food loss and value loss in postharvest agri-food supply chain.

This study conducted longitudinal qualitative research in a developing country with food loss challenges in the postharvest supply chain. This study collected data through multiple rounds of fieldwork, interviews and focus groups over four years. Thematic analysis and “sensemaking” were used for inductive data analysis to generate rich contextual knowledge by drawing upon the lived realities of the agri-food supply chain actors.

First, this study finds that the value losses are varied in the supply chain, encompassing production value, intrinsic value, extrinsic value, market value, institutional value and future food value. This happens through two cumulative effects including multiplier losses, where losses in one model cascade into others, amplifying their impact and stacking losses, where the absence of data stacks or infrastructure pools hampers the realisation of food value. Thereafter, this study proposes four strategies for moving from the loss-incurring current business model to a networked SBM for mitigating losses. This emphasises the need to redefine ownership as stewardship, enable formal and informal beneficiary identification, strengthen value addition and build capacities for empowering communities to benefit from networked SBM with AIS initiatives. Finally, this study puts forth ten propositions for future research in aligning AIS with networked SBM.

This study contributes to understanding the interplay between AIS and SBM; emphasising the integration of the two to effectively address food loss challenges in the early stages of agri-food supply chains. The identified strategies and research propositions provide implications for researchers and practitioners seeking to accelerate sustainable practices for reducing food loss and waste in agri-food supply chains.

This paper aims to investigate infant sensory patterns and their associations with previous perinatal loss, maternal-foetal attachment and postnatal maternal sensory patterns.

In a prospective cohort study, women with and without perinatal loss (N = 57) were recruited from an Australian public hospital. Participants were surveyed during pregnancy (maternal-foetal attachment, loss) and again postnatally (maternal/infant sensory patterns). Chi-square tests and logistic regression analyses controlling for previous perinatal loss were conducted with infant sensory patterns as outcome variables.

“More than typical” infant low registration was associated with poorer quality of maternal-foetal attachment. “More than typical” infant sensory seeking was associated with previous perinatal loss and higher levels of maternal sensory seeking. “More than typical” infant sensory sensitivity was linked with previous perinatal loss, poorer quality of maternal-foetal attachment and higher maternal low registration. “More than typical” infant sensory avoidance was associated with poorer quality of maternal-foetal attachment and higher levels of maternal sensory sensitivity.

To support more typical infant sensory patterns, results point to the potential benefit of occupational therapists supporting pregnant women with previous perinatal loss; facilitating favourable maternal-foetal attachment; and educating new mothers on how their sensory patterns impact on interactions with their infant. Sensory modulation strategies that consider the sensory patterns of both mother and infant may be beneficial to promote engagement in co-occupations.

These findings are the first to suggest that previous perinatal loss, poorer quality of maternal-foetal attachment and higher levels of maternal postnatal sensory patterns represent risk factors for infant sensory patterns that are “more than typical.”

This study aims to develop a high-quality impairment loss allowance model in conformity with Indonesian Financial Accounting Standards 71 (PSAK 71) that has significant contribution to national interests and the banking industry.

The determination of the impairment loss allowance model is settled through 7 stages, using integration of some statistical methods such as Markov chain, exponential smoothing, time series analysis of behavioral inherent trends of probability of default, tail conditional expectation and Monte Carlo simulation.

The model which is developed by the authors is proven to be a high-quality and reliable model. By using the model, it can be shown that the implementation of the expected credit losses model on Indonesian Financial Accounting Standards 71 is more prudent than the implementation of the incurred loss model on Indonesian Financial Accounting Standards 55.

Determination of defaults was based on days past due, and the analysis in this study did not touch the aspects of hedge accounting in general.

This developed model will contribute significantly to national interests as a source of reference for other banks operating in Indonesia in calculating impairment loss allowance (CKPN) and can be used by the Financial Services Authority of Indonesia (OJK) as a guideline in assessing the formation of impairment loss allowance for banks operating in Indonesia.

As so far there is not yet an available standardized model for calculating impairment loss allowance on the basis of Indonesian Financial Accounting Standards 71, the model developed by the authors will be a new breakthrough in Indonesia.

This study aims to examine whether International Financial Reporting Standards (IFRS) convergence process adds value to the accounting quality dimensions, including accruals quality, earnings smoothing, timely loss recognition and earnings persistence.

It analyzes the hypothesis of accounting quality changes in post-IFRS convergence by using the univariate and multivariate statistics. Particularly, the authors rely on panel data analyses using industrial companies’ data from 2008 until 2014, comprising 3,861 firm-years observations, in Indonesia.

The results indicate that there is no conclusive evidence that all accounting quality dimensions including accruals quality, earnings smoothing, timely loss recognition and earnings persistence increased in post-IFRS convergence.

The findings of this study may help regulators and standard setters to consider future adoption of IFRS, mostly to figure out the best “formula” to increase the usefulness of accounting information in post-IFRS convergence.

Rather than doing piecemeal work, the current study focuses on IFRS convergence on a broader aspect of accounting quality dimensions. It also focuses on the convergence process of IFRS as an alternative of full adoption, which has been the focus of many research studies.

The Overall Equipment Effectiveness (OEE) is considered a standard for measuring equipment productivity in terms of efficiency. Still, Artificial Intelligence solutions are rarely used for analyzing OEE results and identifying corrective actions. Therefore, the approach proposed in this paper aims to provide a new rule-based Machine Learning (ML) framework for OEE enhancement and the selection of improvement actions.

Association Rules (ARs) are used as a rule-based ML method for extracting knowledge from huge data. First, the dominant loss class is identified and traditional methodologies are used with ARs for anomaly classification and prioritization. Once selected priority anomalies, a detailed analysis is conducted to investigate their influence on the OEE loss factors using ARs and Network Analysis (NA). Then, a Deming Cycle is used as a roadmap for applying the proposed methodology, testing and implementing proactive actions by monitoring the OEE variation.

The method proposed in this work has also been tested in an automotive company for framework validation and impact measuring. In particular, results highlighted that the rule-based ML methodology for OEE improvement addressed seven anomalies within a year through appropriate proactive actions: on average, each action has ensured an OEE gain of 5.4%.

The originality is related to the dual application of association rules in two different ways for extracting knowledge from the overall OEE. In particular, the co-occurrences of priority anomalies and their impact on asset Availability, Performance and Quality are investigated.

This study empirically tests the use of loan loss provisions (LLPs) for earnings and capital smoothing when emphasis is laid on banks' riskiness and adoption of the International Financial Reporting Standards (IFRSs) in Nigeria.

Annual bank-level data are hand-extracted between 2007 and 2017 from annual reports of a sample 16 deposit money banks (DMBs), and analysed using appropriate panel regression models subsequent to a number of diagnostic tests including heteroscedasticity, autocorrelation and cross-sectional dependence. The use of both reported LLPs (TLLP) and discretionary LLPs (DLLP) for earnings and capital management is tested to advance the practice in the literature.

Generally, the study finds that Nigerian DMBs manage capital via LLPs, while mixed results are obtained for earnings smoothing. However, during IFRS, Nigerian DMBs' management of capital is identifiable with TLLP, while smoothing of earnings is peculiar to DLLP. Additionally, evidence of the improvement in loan loss reporting quality expected during IFRS for riskier Nigerian DMBs, could not be attained. This is corroborated by the study's findings of the use of both TLLP and DLLP for earnings and capital management during IFRS by DMBs in solvency crisis against the only use of TLLP to manage capital found for the entire period.

The evidential capital and earnings lopsidedness may subject Nigerian DMBs' going-concern to a lot of questions.

The study sets a foremost record in the empirical test of managerial opportunistic behaviour embedded in earnings and capital concurrently while accounting for loan losses by all categories of Nigerian DMBs in terms of riskiness, following accounting regime change.

This study aims to determine the influence of bruise damage generated from the impact test on the physical, chemical and nutritional responses of tomato fruit.

The impact loading was applied from different heights. The impact energies for 20, 40 and 60 cm drop heights were 129.59, 259.18 and 388.77 mJ, respectively. The injured samples were kept for 48 hours at low (10 °C) and ambient (22 °C) storage temperatures. Weight loss, firmness, color, total soluble solids (TSS), lycopene and carotenoids were measured before the impact test (day 0) and after 48 hours of the impact and storage.

The drop height of 60 cm and storage at 22 °C showed the highest values in the bruised area. The impact from the 60 cm drop height significantly reduced weight, lightness, yellowness, hue, firmness, lycopene and carotenoids, particularly at 22 °C storage condition. Redness (a*) and color index (CI) showed a remarkable increase (p < 0.05) at 22 °C on tomatoes affected from the highest impact level (388.77 mJ) after 48 hours of storage. No pronounced significance was seen between TSS and drop heights. This study has confirmed that tomato bruising for a short-term storage period induces physiological changes at different storage temperature conditions.

The study can confirm the crucial role of inappropriate handling in increasing fresh produce loss within short-term storage. Also, this research can be considered as a guideline for transporters, handlers, processors, distributors and horticulture researchers in the fresh produce supply chain during postharvest operations.