Biomedical Machine Maintenance Scheduling

Tissue banks procure approximately 45,000 tissue donations per year, providing nearly 9,000,000 individuals (about half the population of New York) with life-enhancing and life-saving medical procedures. Proper biobank machine maintenance is imperative to this process. Mandatory forms of maintenance are critical to avoid unexpected malfunctions, which can halt operations and render samples unusable. Each machine has a unique reliability rate within the system; although some can quickly be repaired or replaced, many processes rely on limited machinery where even planned downtime can significantly influence the tissue processing. AlloSource, one of the largest tissue manufacturers in the United States, too often schedules these preventive events unnecessarily or inconveniently, resulting in machines breaking down at inopportune times. In response to these inefficiencies we ask, “What is the best consolidated and standardized equipment maintenance schedule that maximizes monthly maintenance events to ensure increased equipment availability while meeting the demand of the biomedical manufacturing network?” We use an optimization model to consider equipment reliability, downtime, availability, and demand to develop a preventive maintenance schedule. Our model focuses on scheduling the maximum number of events the maintenance crew can conduct each month to ensure vital equipment to the allograft process is available, which provides more opportunities for tissue therapies. In doing so, the maintenance crew is also able to complete more events, driving up annual throughput while driving down equipment downtime.

Bench Testing of Sensors Utilized for In-Line Monitoring of Lubricants and Hydraulic Fluids Properties

This work reports the results of a study on the behaviour of five sensors recently developed for oil conditions monitoring, installed in-line in an experimental test rig for lubricants. The tests were carried out on seven oils of different origins (one synthetic ester, two bio-based synthetic esters, four vegetable oils) and use (two UTTOs and five hydraulic oils), under controlled working conditions, according to a specially designed test method. At first, the study concerned the identification of the conditions for the correct sensors’ installation. Then, the tests started applying to the fluids severe work cycles intended to accelerate oil ageing. The data of viscosity, permittivity, relative humidity, electric conductivity, particle contamination, and ferro-magnetic particles provided by the sensors were compared to the results of laboratory analyses made on oil samples taken during the tests with the aim of verifying the sensors measurements accuracy and reliability and selecting the more suitable ones to in-line oil conditions monitoring, in the perspective of introducing them also in field applications, e.g., on agricultural tractors, for preventing damages due to oil deterioration, and in managing the machine maintenance.

PREDICTIVE MAINTENANCE IMPLEMENTATION OF AUTOCLAVE REACTOR AGITATOR

Machines are an important factor in the industrial world to produce a product in a company. PT. XYZ is a company engaged in the food industry for sweeteners processed from tapioca flour and corn flour where, through research observations, data is obtained that there are problems that are often faced such as damage to the Agitator Autoclave machine, unavailability of spare parts ( spare parts) needed when there is a breakdown and a breakdown schedule for maintenance workers who have to work overtime. The purpose of this study is to determine the current condition of machine maintenance to reduce damage or failures, the level of machine effectiveness and provide alternative solutions to increase machine effectiveness. The research method used is quantitative using the Overall Equipment Effectiveness (OEE) method, Six Big Losses, Failure Modes and Effects Analysis. The results of the study resulted in an Overall Equipment Effectiveness (OEE) value of 75.07%. The low OEE value on the Agitator Autoclave machine is due to the low performance factor because the engine speed does not match its ideal speed and also the low idle and minor losses in the losses factor caused by frequent breakdowns. Suggestions and suggestions that can be recommended are to periodically evaluate machines and replace old machines.

Classification Methods for Motor Vibration in Predictive Maintenance

Reducing costs is an important part in todays business. Therefore manufacturers try to reduce unnecessary work processes and storage costs. Machine maintenance is a big, complex, regular process. In addition, the spare parts required for this must be kept in stock until a machine fails. In order to avoid a production breakdown in the event of an unexpected failure, more and more manufacturers rely on predictive maintenance for their machines. This enables more precise planning of necessary maintenance and repair work, as well as a precise ordering of the spare parts required for this. A large amount of past as well as current information is required to create such a predictive forecast about machines. With the classification of motors based on vibration, this paper deals with the implementation of predictive maintenance for thermal systems. There is an overview of suitable sensors and data processing methods, as well as various classification algorithms. In the end, the best sensor-algorithm combinations are shown.

Analisis Produktivitas Mesin Filling Auto Cup Sealer 1 dengan Metode Overall Equipment Effectiveness pada PT. Prima Kemasindo

The high level of downtime on the ACS 1 filling machine at PT. Prima Kemasindo causes the production process to be not optimal on the machine. The purpose of this study is to identify the maintenance system on the ACS 1 filling machine and measure the productivity level of the ACS 1 filling machine in the period from January to March 2021. This research is applied research using the Overall Equipment Effectiveness (OEE) method. The data used in this study are primary and secondary data obtained from company reports as well as interviews and observations. The results obtained in this study are the Overall Equipment Effectiveness (OEE) value of the ACS 1 filling machine for the period January 98.0%, February 98.5%, March 95.2%, and the average OEE value for the January-March period is 97.2 %. Then from the analysis of Six Big Loses, it is known that the highest loss elements are Idling and Mirror Stoppages and Reduced Speed. Based on the results of the fishbone diagram, it is known that the cause of Idling and Mirror Stoppages and Reduced Speed consists of several factors, namely humans, machines, materials, and methods. Several efforts can be made to increase the effectiveness of the use of machines, namely periodic replacement of machine maintenance, periodic operator training, and training on operator self-awareness, the importance of supervision, and operators must always supervise machine parts.

Investigation of the properties of composite materials based on epoxy resins with microsilica additives

The outcomes of studying epoxy-based composite materials supplemented with microsilica are provided in the article. Microsilica was used as a filler. The samples were produced on the epoxy ED-20 basis supplemented with 2, 5 and 10 mas. % of microsilica. The structure and size of finely dispersed filler particles were defined. The obtained composites were tested for resistance to the effect of variable temperatures, corrosive, and abrasion. The study outcomes proved that samples supplemented with 2% of microsilica are more resistant to acid and alkali as well as to petrol than those ones supplemented with 25% of microsilica. Besides the amount of the filler from 2 to 10% doesn’t sufficiently affect the resistance to variable temperatures. When microsilica is added to epoxy resin, it causes scuff resistance increase. The conducted testing proved that the developed composite materials are resistant to the effect of variable temperatures, corrosive, and abrasion. This enables to use these materials as coatings and anti-corrosion protection during machine maintenance.

Application of Multidimensional Statistical Analysis in Tribotechnical Diagnostics of Hydraulic Fluids in Woodworking Equipment

The article dealt with the assessment of the quality of hydraulic oil and determination of the mode of wear of the friction surfaces of Baljer & Zembrod manipulating lines through the information traces in the oils by applying tribotechnical diagnostics. We presented the assessment of the level of degradation of the oils. In addition, we presented the mode of wear of the friction surfaces washed in oil through evaluation of the qualitative and quantitative characteristics of the particles found in the oil. In detail, we focused on the application of suitable multivariate statistical methods on the data matrix. The article also presents predictive models that can sort oils into groups based on the assessment of quality of the oil and the state of the friction couples. The models can be used in research and in solving practical tasks in tribotechnical diagnostics of hydraulic fluids in woodworking equipment. Our results showed that the manipulation lines were greatly thermically stressed due to inadequate oil and machine maintenance. By correlative integration of all methods used, we could determine the real mode of the wear of the tribologic nodes of the machine. The experiment enabled the early detection of an undesirable process in the tribological node and implementation of corrective measures before the machine would break down.

Maintenance Preventive Scheduling of Critical Components in Offset Printing Machine (Case Study : PT. XYZ)

Maintenance activities are generally considered as supporting activities in the production process. However, this activity is very important because it contributes directly to the smooth running of the production process and productivity. PT. XYZ is a company engaged in mass media or newspapers since September 8, 2015. In the newspaper production process, PT. XYZ experienced delays in the production process due to damage to the component parts of the printing machine, in which the Offset printing machine is the core printing machine that is always used to print newspapers. Based on data on the frequency of damage during 2020 which was obtained from observations and interviews with operators, damage to machine components for 1 year on the offset printing machine counted 73 times that it was damaged. Thus making the machine stop operating from the effective working time of the machine, which is 264 days/year. This is due to the unavailability of a machine maintenance schedule because the company is still implementing a breakdown maintenance system. Thus the researcher aims to calculate the value of the identified critical components and calculate the effective time of machine operation for scheduling replacement of critical components of offset printing machines using the Reliability Centered Maintenance method. Based on the results of data processing using the Reliability Centered Maintenance method, the contactor component is determined as a critical component where the value of the Risk Priority Number is 72 with an average checking time of 11,250 minutes and component replacement time of 7 times/year. For this reason, it can be concluded that the contactor is a critical component with a damage value of 72 and the scheduling time for component replacement is 7 times in 1 year.