Equipment Categories Research Articles

Current State of the Capital Investment Account in Enterprises and Directions for Its Improvement

The article examines the situation of capital investments in businesses today, pointing out problems with capital investment accounting and offering solutions by implementing global standards in the face of the expanding digital economy. The inefficiency of describing capital investment records for various asset kinds, which restricts openness and decision-making usefulness, is one of the major information gaps that has been found. The study's methodology includes a comparative analysis, economic analysis, and data from "Saturn Metalworking LLC" to examine capital investment methods. Results indicate that consistent accounting practices obfuscate precise information about investments in certain assets. One suggestion is to improve accounting procedures to make it easier to track spending in modernization, construction, and various equipment categories. By optimizing capital investment records, these changes hope to enhance stakeholder knowledge and strategic resource allocation in a digital economy.

Assessment of Bitumen Paver and HMP Efficiency for a Road Project

One of the important and dependable sectors of the national economy is the equipment used in highway construction. In the process of building constructions, efficient utilization of labour, supplies, and machinery must be fervently pursued through competent project management. The adoption of innovative procedures and new equipment has resulted in a dramatic advance in construction technology in recent decades. The selection of the right type and size of construction equipment typically affects how productive a project is on the job site. Thus, it is essential that site managers and construction planners understand the primary equipment categories that are most frequently used in construction. Technical aspects and working conditions are taken into consideration in the article's method of calculating the operational productivity and cost of asphalt pavers. This increases the accuracy of decisions made about how to organize and manage highway maintenance activities on Chikhali-Tarsod NH-6.

Comparative Analysis of the Medical Equipment Management Process in Colombo Gampaha and Kaluthara Districts

Comparative Analysis of the Medical Equipment Management Process in Colombo Gampaha and Kaluthara Districts

Comprehension of international safety signs: A prospective technical workers context

An effective method for educating workers about occupational hazards is the use of safety signs in the workplace. However, workers' understanding may vary due to factors such as cultural background, familiarity, and training. This study aimed to assess the comprehension of international safety signs among participants representing the prospective technical workforce in Indonesian industries. Two groups of participants (n = 71), comprising vocational high school students and college-level engineering students, were involved to assess their comprehension of symbol elements, comprehension of complete signs, compliance intention, and familiarity towards a selected set of international safety signs. The study revealed that the complete signs significantly increased the comprehension and compliance intention of the prospective technical workers regarding the selected signs (p < .001). However, most safety signs under the fire equipment and safe condition categories investigated in the study had low comprehension and compliance intention scores (<67%). Conversely, signs under the mandatory and warning categories generally exhibited better comprehension and compliance intention scores. Additionally, participants in the study were generally not familiar with the investigated signs (<50%). The familiarity with the signs was strongly correlated with the comprehension and compliance intention of the participants (p < .001). Relevance to industryUnderstanding the findings, which revealed that the comprehension, compliance intention, and familiarity of the prospective technical worker participants with some international safety signs generally did not meet the standards, interventions such as training and redesigning the safety signs are highly recommended to minimize future adverse safety outcomes when they enter the workforce.

Machine learning-based radiotherapy time prediction and treatment scheduling management.

The utility efficiency of medical devices is important, especially for countries such as China, which have a large population and shortage of medical care resources. Radiotherapy devices are among the most valuable and specialized equipment categories and carry enormous treatment loads. In this study, a novel method is proposed to improve the efficiency of a radiotherapy device (linac). Although scheduling management with accurate prediction of the entire treatment time included in each appointment, arrange a reasonable time duration for appointments and save time between patient shifts effectively. Tasks belonging to the treatment and non-treatment groups can be assigned more flexibly based on the availability of time. Data from 1665 patients, including patient positioning time (PT) and treatment time (TT), were collected in collaboration with the Radiotherapy Center of the Department of Oncology at the Second Affiliated Hospital of Kunming Medical University from November 2020 to August 2021. The features related to PT and TT were extracted and used to train the machine learning-based model to predict PT and TT in independent patients. The prediction results were subsequently applied to a minute-based scheduling tool. Artificial intelligence is a promising approach to solve abstract problems with a specialized knowledge background. The results of this study show encouraging prediction outcomes in relation to effective scheduling management and could improve the efficiency of the linac. This successful trial broadens the meaning of medical data and potential future research directions in radiotherapy.

A Heuristic Integrated Scheduling Algorithm via Processing Characteristics of Various Machines

Complex products with a tree-like structure usually have an asymmetric structure. Therefore, in order to avoid the separation of equipment and operation correlation during the scheduling, the structural attributes of products and the use of equipment resources should be fully considered. However, this feature is ignored in the current research works on the scheduling of multi-variety and small batch products. This leads to increased idle time for equipment and an extended makespan for products. To avoid this situation, a heuristic integrated scheduling algorithm via processing characteristics of various machines (HIS-PCVM) is proposed. In the integrated scheduling, the algorithm first divides the equipment into two categories: the special equipment and the general equipment according to the resources of the production scheduling system. Then, different scheduling methods are designed according to the equipment categories. The makespan of the product is further optimized through various combination methods. Moreover, the constraint audit strategy to guarantee the constraint relationship between the operations is optimized. The earliest scheduling time strategy is proposed to improve the parallelism and serial tightness of the operations. These strategies reduce the idle time of equipment effectively. Experimental results show that the proposed algorithm has a better application effect in reducing the makespan of complex products, both with asymmetric structures and symmetric structures. This also shows that the algorithm is effective in improving the utilization rate of equipment.

Distractions in the operating room: a survey of the healthcare team.

BackgroundDistractions during surgical procedures are associated with team inefficiency and medical error. Little is published about the healthcare provider’s perception of distraction and its adverse impact in the operating room. We aim to explore the perception of the operating room team on multiple distractions during surgical procedures.MethodsA 26-question survey was administered to surgeons, anesthesia team members, nurses, and scrub technicians at our institution. Respondents were asked to identify and rank multiple distractions and indicate how each distraction might affect the flow of surgery.ResultsThere was 160 responders for a response rate of 19.18% (160/834), of which 71 (44.1%) male and 82 (50.9%) female, 48 (29.8%) surgeons, 59 (36.6%) anesthesiologists, Certified Registered Nurse Anesthetists (CRNA), and 53 (32.9%) OR nurses and scrub technicians. Responders were classified into a junior group (< 10 years of experience) and a senior group (≥ 10 years). Auditory distraction followed by equipment were the most distracting factors in the operating room. All potential auditory distractions in this survey were associated with higher percentage of certain level of negative impact on the flow of surgery except for music. The top 5 distractors belonged to equipment and environment categories. Phone calls/ pagers/ beepers and case relevant communications were consistently among the top 5 most common distractors. Case relevant communications, music, teaching, and consultation were the top 4 most perceived positive impact on the flow of surgery. Distractors with higher levels of “bothersome” rating appeared to associate with a higher level of perceived negative impact on the flow of surgery. Vision was the least distracting factor and appeared to cause minimal positive impact on the flow of surgery.ConclusionsTo our knowledge, this is the first survey studying perception of surgery, anesthesia, and OR staff on various distractions in the operating room. Fewer unnecessary distractions might improve the flow of surgery, improve OR teamwork, and potentially improve patient outcomes. Supplementary InformationThe online version contains supplementary material available at 10.1007/s00464-022-09553-8.

Off-Road Construction and Agricultural Equipment Electrification: Review, Challenges, and Opportunities

Though the current wave of electric vehicles is transforming the on-road passenger and commercial vehicle fleets, similar attempts in the off-road equipment sector appear to be lacking. Because of the diverse equipment categories and varied applications, electrifying off-road equipment requires significant research and development. A successful electrification of such equipment can offer an array of benefits, including reduced air and noise pollution, higher energy efficiency, and increased productivity. This paper provides a review of the current state of technology in off-road equipment electrification, with a focus on the equipment used in construction and agricultural applications. The paper also discusses advantages of, and challenges associated with, electrifying off-road construction and agricultural equipment. In addition, potential solutions for overcoming these challenges as well as opportunities to facilitate the electrification of off-road construction and agricultural equipment are identified.

Recognizing Design Issues in Process Industry for Safer Design

Recognizing Design Issues in Process Industry for Safer Design

The complexity of providing humanitarian surgical care in armed conflict: a framework to help categorize needs

Abstract Armed conflicts are increasing globally due to political unrest and the broader effects of climate change. Without resources to provide quality surgical care, it becomes nearly impossible to provide quality emergency surgery and trauma care similar to that in high-income countries. To understand and help aid organizations provide resources and address the surgical needs of populations facing armed conflict, a matrix to identify variables and help with interventions was envisioned. A previously published global surgery matrix based on the PIPES (Personnel, Infrastructure, Procedures, Equipment and Supplies) surgical capacity tool was adapted to this context. The novel matrix incorporates 108 variables. These variables are grossly divided into local and international agency components to address the issue of who is providing care. Using a time continuum of pre-conflict, conflict, and post-conflict allows organizations to concentrate on when during the conflict to target their intervention. In addition to the previously used personnel, infrastructure, procedures, equipment, and supplies categories, a sixth category called standards was included that addresses the issues such as information technology, data systems, quality improvement programs, and patient safety. Pilot testing of this matrix to obtain feedback from end users is the next step in development. Ultimately, peri-conflict preparedness should increase and improve surgical outcomes and reduce in death and disabilities around the world.

Hospital-wide cardiac arrest in situ simulation to identify and mitigate latent safety threats

BackgroundCardiac arrest resuscitation requires well-executed teamwork to produce optimal outcomes. Frequency of cardiac arrest events differs by hospital location, which presents unique challenges in care due to variations in responding team composition and comfort levels and familiarity with obtaining and utilizing arrest equipment. The objective of this initiative is to utilize unannounced, in situ, cardiac arrest simulations hospital wide to educate, evaluate, and maximize cardiac arrest teams outside the traditional simulation lab by systematically assessing and capturing areas of opportunity for improvement, latent safety threats (LSTs), and key challenges by hospital location.MethodsUnannounced in situ simulations were performed at a city hospital with multidisciplinary cardiac arrest teams responding to a presumed real cardiac arrest. Participants and facilitators identified LSTs during standardized postsimulation debriefings that were classified into equipment, medication, resource/system, or technical skill categories. A hazard matrix was used by multiplying occurrence frequency of LST in simulation and real clinical events (based on expert opinion) and severity of the LST based on agreement between two evaluators.ResultsSeventy-four in situ cardiac arrest simulations were conducted hospital wide. Hundreds of safety threats were identified, analyzed, and categorized yielding 106 unique latent safety threats: 21 in the equipment category, 8 in the medication category, 41 in the resource/system category, and 36 in the technical skill category. The team worked to mitigate all LSTs with priority mitigation to imminent risk level threats, then high risk threats, followed by non-imminent risk LSTs. Four LSTs were deemed imminent, requiring immediate remediation post debriefing. Fifteen LSTs had a hazard ratio greater than 8 which were deemed high risk for remediation. Depending on the category of threat, a combination of mitigating steps including the immediate fixing of an identified problem, leadership escalation, and programmatic intervention recommendations occurred resulting in mitigation of all identified threats.ConclusionsHospital-wide in situ cardiac arrest team simulation offers an effective way to both identify and mitigate LSTs. Safety during cardiac arrest care is improved through the use of a system in which LSTs are escalated urgently, mitigated, and conveyed back to participants to provide closed loop debriefing. Lastly, this hospital-wide, multidisciplinary initiative additionally served as an educational needs assessment allowing for informed, iterative education and systems improvement initiatives targeted to areas of LSTs and areas of opportunity.

Clustering Mining Equipment Productivity Data Using K-Means Algorihtm

There are many factors that affect the productivity of mining equipment, one of which is the condition of the mining equipment when it is used. Knowing the condition of the machines on mining equipment is mandatory for supervisors in mining activities. In analyzing data on the condition of mining equipment in large quantities requires a lot of energy and time, so a classification model is needed that can categorize the mining equipment based on its performance. Data Mining is a process that uses statistical, mathematical, artificial intelligence and machine learning techniques to extract information. The results of data mining for mining productivity data are obtained duration of mining equipment work has a impact on productivity based on correlation value between work duration and maintenance duration of a tool. Data mining analysis is also carried out by clustering mining equipment using the K-Means model. The results obtained a conclusion that supports mining equipment with less working duration affects to productivity. The result shows variables that affect the productivity of mining equipment and divide mining equipment categories based on tool performance with data mining clustering techniques.

Analysis of agricultural exports based on deep learning and text mining.

Agricultural exports are an important source of economic profit for many countries. Accurate predictions of a country’s agricultural exports month on month are key to understanding a country’s domestic use and export figures and facilitate advance planning of export, import, and domestic use figures and the resulting necessary adjustments of production and marketing. This study proposes a novel method for predicting the rise and fall of agricultural exports, called agricultural exports time series-long short-term memory (AETS-LSTM). The method applies Jieba word segmentation and Word2Vec to train word vectors and uses TF-IDF and word cloud to learn news-related keywords and finally obtain keyword vectors. This research explores whether the purchasing managers’ index (PMI) of each industry can effectively use the AETS-LSTM model to predict the rise and fall of agricultural exports. Research results show that the inclusion of keyword vectors in the PMI values of the finance and insurance industries has a relative impact on the prediction of the rise and fall of agricultural exports, which can improve the prediction accuracy for the rise and fall of agricultural exports by 82.61%. The proposed method achieves improved prediction ability for the chemical/biological/medical, transportation equipment, wholesale, finance and insurance, food and textiles, basic materials, education/professional, science/technical, information/communications/broadcasting, transportation and storage, retail, and electrical and machinery equipment categories, while its performance for the electrical and optical categories shows improved prediction by combining keyword vectors, and its accuracy for the accommodation and food service, and construction and real estate industries remained unchanged. Therefore, the proposed method offers improved prediction capacity for agricultural exports month on month, allowing agribusiness operators and policy makers to evaluate and adjust domestic and foreign production and sales.

Analiza organizacije rada dijaliznih centara tokom epidemije COVID-19 infekcije u Srbiji

Monitoring and assessment of the implementation of the National Program of Prevention, Treatment, Advancement and Control of Renal Insufficiency and Dialysis Development in the Republic of Serbia by 2020 has been implemented by the Institute of Public Health of Serbia "Dr Milan Jovanović Batut". As the mode of dialysis centres operation changed after the COVID-19 epidemic was proclaimed, whereby some centres started operating in the Covid-regime, while Covid-negative patients from these centres were rerouted to the closest dialysis centres with available capacities, the need for monitoring and assessing the conditions for the implementation of the chronic dialysis program was further emphasized. The purpose of this paper is to provide a retrospective analysis of the conditions for the implementation of a chronic dialysis program in healthcare institutions within, and outside of the Network Plan during the COVID-19 outbreak in the period from the beginning of the epidemic to 1 October 2021. For the purposes of this study, a special questionnaire was designed, which was filled in by dialysis centres. The questionnaire consisted of three parts pertaining to: a) implementation of infection prevention measures at the dialysis centre, b) availability of personal protection equipment and disinfectants at the dialysis centres during the COVID-19 pandemic and c) conditions for the provision of dialysis services to patients positive for, or suspected of, COVID-19 infection. In the observed period, as much as 39% of the dialysis centres were designated to receive patients from other healthcare institutions, which called for additional efforts in organising and pursuing transmission containment. Implementation of transmission prevention measures in the dialysis centres was maintained at a very high level (between 95.5 and 100%). Only 10-15% of dialysis centres reported occasional shortages of individual items from the personal protective equipment or disinfectant categories. Almost one in five dialysis centres received a higher number of patients during the outbreak than was the case in the pre-pandemic period. In that sense, it was difficult to maintain the necessary physical distance in an already limited space, and to organize work in shifts as human resources were restricted. In addition to the general documents pertaining to infectious disease transmission prevention and containment, a protocol needed to be elaborated to organize the operation of dialysis centres in an outbreak such as the one caused by the SARS-CoV-2 virus.

DOES THE LEVEL AND SEVERITY OF INJURY AFFECT PATIENT SATISFACTION IN PATIENTS WITH CHRONIC SPINAL CORD INJURY UNDERGOING INPATIENT REHABILITATION ?

OBJECTIVE: This study aimed to investigate whether the level of satisfaction differed regarding the level and severity of injury in patients with chronic spinal cord injury (SCI) treated on an in-patient setting and whether patients with different satisfaction levels had distinct functional independence and health related quality of life (HRQoL) measures.MATERIAL AND METHODS: The SCI level (cervical, thoracic, lumbosacral) of the patients was recorded, and the severity of SCI (incomplete,complete) was determined according to the American Spinal Cord Injury Association (ASIA) Impairment Scale. The degree of functional independence of the patients was determined using the Functional Independence Measure (FIM) motor score. HRQoL was assessed using the Short Form-36 (SF-36). Satisfaction was assessed using a questionnaire instituted to evaluate patient satisfaction. Satisfaction with the physician, nurse, physiotherapist, catering, cleaning service, technical equipment categories and the overall satisfaction were questioned and satisfaction levels were determined as ”very satisfied, satisfied, dissatisfied, very dissatisfied”.RESULTS: 84 patients with chronic SCI were included in this cross-sectional study. Regarding the level of SCI, 19 patients had cervical (mean age:36.3±14.5, 78.9% male), 52 had thoracic (mean age: 32.1±13.6, 61.5% male), 13 had lumbosacral SCI (mean age: 38.8±20, 61.5% male). Regarding the severity of SCI, 36 patients had complete (mean age: 34±13, 77.7% male), 48 had incomplete (mean age: 35±15, 56.2% male) injury. There was no significant difference between cervical, thoracic and lumbosacral SCI groups in satisfaction categories. However, when the groups were compared in regard to the severity of SCI, patients with incomplete SCI had higher rates for satisfaction with the physician and technical equipment (p=0.03 and p=0.02, respectively). No significant difference was found in the other categories. Regarding the overall satisfaction, there was no significant difference in HRQoL and functional independence of the patients grouped according to their satisfaction levels.CONCLUSIONS:Patients with incomplete SCI had higher satisfaction level with the physician and technical equipment. Although characteristics of injury are distinct, if the expectations are met similar satisfaction rates may be obtained in patients with chronic SCI. More comprehensive studies are needed in terms of other patient-related variables that affect patient satisfaction.

Public Opinion About Police Weapons and Equipment: An Exploratory Analysis

Despite debates about the “material militarization” of the police, relatively little information on mass public opinion about police weapons, equipment, and gear currently exists. We analyze data from a national, opt-in panel of survey participants to assess public opinion regarding police use of 10 different types of weapons and equipment for use in confrontations with citizens. We find that public opinion defies easy classification into “militarized” versus “routine” equipment categories. Multivariate analyses indicate that perceptions of (a) police efficacy and (b) the frequency with which officers experience physical assaults on the job are the most consistent predictors of support for a range of weapons and gear, whereas perceptions of police misconduct and bias predict opposition to some types of tools. Partisan differences in attitudes between Democrats, Republicans, and Independents are less consistent predictors than broader perceptions about policing, but the effects of partisanship that are evident are substantively large.

Economic Depreciation of In-Woods Forestry Equipment in the US South

Abstract Forestry machines sold at auctions across the southern United States covering the years 2005 to 2019 (n = 640) were compiled into three equipment categories—rubber-tired feller bunchers, grapple skidders, and trailer-mounted loaders—with inflationary effects removed. The data were discounted by a reliability function derived from a two-parameter Weibull distribution, which defined the probability of future operability at machine hours h and a wrecking value based on each machine’s specified worth as scrap. These adjusted salvage values were then transformed using the Box-Cox normal method. Age affected all fellers and certain manufacturers of skidders and loaders. A significant annual use effect was revealed for fellers and skidders. Interactions of age and use with horsepower revealed that machine size influenced buyers’ feller and skidder purchasing decisions. Manufacturer intercept and slope shifters pointed to potential brand recognition by buyers. Perceived quality differences between manufacturers, however, were not revealed. Depreciation occurred at ever-increasing rates over machine lifetime.

The Influence of Machinery and Equipment Degradation on Their Depreciation

The preparation of financial statements in accordance with IFRS involves the choice of such methods of depreciation for assets that are supposed to reflect most accurately the expected pattern of consumption of future economic benefits from the use of assets. However, in relation to machinery and equipment items this requirement is difficult to implement, since it is not clear how to understand and measure the economic benefits associated with such assets and the pattern of their consumption. In our opinion, the consumption of future economic benefits from the use of an asset is reflected in its fair value, and the depreciation of an asset over a period of time expresses a decrease in the fair value of the asset in that period. Having regard to this position, it is necessary to be be choosing such a depreciation method which affords the best correspondence between the carrying amount of assets and their fair values. We show that the often used linear depreciation method does not satisfy this requirement even for an asset that generates equal annual benefits from year to year. The article is devoted to the selection of the most suitable method of depreciation for machinery and equipment items. In our opinion, it is necessary to take into account the dynamics of their degradation processes (deterioration of operational characteristics). In this regard, we provide numerous data on a decrease in productivity and an increase in operating costs with age for various machinery and equipment categories. The analysis of such data allows us to offer a simple linear model of machine impair­ment/de­gradation, as well as a depreciation method based on it. This method turns out to resemble the sum of the years’ digits method and can be considered as a generalization of such a method. Its applicability to measuring the depreciation of real machinery and equipment items is confirmed by the results of economic and mathematical modeling and experimental estimates.

Charting a Roadmap for Value-based Surgery in the Post-pandemic Era.

Charting a Roadmap for Value-based Surgery in the Post-pandemic Era.

A mixed-methods needs assessment of traumatic brain injury care in a low- and middle-income country setting: building neurocritical care capacity at two major hospitals in Cambodia.

The high global burden of traumatic brain injury (TBI) disproportionately affects low- and middle-income countries (LMICs). These settings also have the greatest disparity in the availability of surgical care in general and neurosurgical care in particular. Recent focus has been placed on alleviating this surgical disparity. However, most capacity assessments are purely quantitative, and few focus on concomitantly assessing the complex healthcare system needs required to care for these patients. The objective of the present study was to use both quantitative and qualitative assessment data to establish a comprehensive approach to inform capacity-development initiatives for TBI care at two hospitals in an LMIC, Cambodia. This mixed-methods study used 3 quantitative assessment tools: the World Health Organization Personnel, Infrastructure, Procedures, Equipment, Supplies (WHO PIPES) checklist, the neurosurgery-specific PIPES (NeuroPIPES) checklist, and the Neurocritical Care (NCC) checklist at two hospitals in Phnom Penh, Cambodia. Descriptive statistics were obtained for quantitative results. Qualitative semistructured interviews of physicians, nurses, and healthcare administrators were conducted by a single interviewer. Responses were analyzed using a thematic content analysis approach and coded to allow categorization under the PIPES framework. Of 35 healthcare providers approached, 29 (82.9%) participated in the surveys, including 19 physicians (65.5%) and 10 nurses (34.5%). The majority had fewer than 5 years of experience (51.7%), were male (n = 26, 89.7%), and were younger than 40 years of age (n = 25, 86.2%). For both hospitals, WHO PIPES scores were lowest in the equipment category. However, using the NCC checklist, both hospitals scored higher in equipment (81.2% and 62.7%) and infrastructure (78.6% and 69.6%; hospital 1 and 2, respectively) categories and lowest in the training/continuing education category (41.7% and 33.3%, hospital 1 and 2, respectively). Using the PIPES framework, analysis of the qualitative data obtained from interviews revealed a need for continuing educational initiatives for staff, increased surgical and critical care supplies and equipment, and infrastructure development. The analysis further elucidated barriers to care, such as challenges with time availability for experienced providers to educate incoming healthcare professionals, issues surrounding prehospital care, maintenance of donated supplies, and patient poverty. This mixed-methods study identified areas in supplies, equipment, and educational/training initiatives as areas for capacity development for TBI care in an LMIC such as Cambodia. This first application of the NCC checklist in an LMIC setting demonstrated limitations in its use in this setting. Concomitant qualitative assessments provided insight into barriers otherwise undetected in quantitative assessments.