Operational Planning of Maintenance Measures by Means of Event-driven Simulation

AbstractModern manufacturing systems are characterized by an increasing complexity and high dynamic. This leads to new challenges for the operational planning of maintenance and production. This paper introduces a novel approach to an online simulation which enables a cost-optimized integration of condition-based maintenance measures in the production plan. The dynamic approach is implemented by means of event-driven simulation. It enables to depict the actual state of a complex manufacturing system, to simulate the future development of the production and thereby to evaluate different planning alternatives of maintenance

Analysis of the visually detectable wear progress on ball screws

The actual progression of pitting on ball screw drive spindles is not well known since previous studies have only relied on the investigation of indirect wear effects (e. g. temperature, motor current, structure-borne noise). Using images from a camera system for ball screw drives, this paper elaborates on the visual analysis of pitting itself. Due to its direct, condition-based assessment of the wear state, an image-based approach offers several advantages, such as: Good interpretability, low influence of environmental conditions, and high spatial resolution. The study presented in this paper is based on a dataset containing the entire wear progression from original condition to component failure of ten ball screw drive spindles. The dataset is being analyzed regarding the following parameters: Axial length, tangential length, and surface area of each pit, the total number of pits, and the time of initial visual appearance of each pit. The results provide evidence that wear development can be quantified based on visual wear characteristics. In addition, using the dedicated camera system, the actual course of the growth curve of individual pits can be captured during machine operation. Using the findings of the analysis, the authors propose a formula for standards-based wear quantification based on geometric wear characteristics

Analysis of the Visually Detectable Wear Progress on Ball Screws

The actual progression of pitting on ball screw drive spindles is not well known since previous studies have only relied on the investigation of indirect wear effects (e. g. temperature, motor current, structure-borne noise). Using images from a camera system for ball screw drives, this paper elaborates on the visual analysis of pitting itself. Due to its direct, condition-based assessment of the wear state, an image-based approach offers several advantages, such as: Good interpretability, low influence of environmental conditions, and high spatial resolution. The study presented in this paper is based on a dataset containing the entire wear progression from original condition to component failure of ten ball screw drive spindles. The dataset is being analyzed regarding the following parameters: Axial length, tangential length, and surface area of each pit, the total number of pits, and the time of initial visual appearance of each pit. The results provide evidence that wear development can be quantified based on visual wear characteristics. In addition, using the dedicated camera system, the actual course of the growth curve of individual pits can be captured during machine operation. Using the findings of the analysis, the authors propose a formula for standards-based wear quantification based on geometric wear characteristics

Improving predictive maintenance benefits from online monitoring of spindles: case study in woodworking machine tool

Objective: This article aims to present a case study of the application of an online monitoring system for spindles in a furniture industry, analyzing the benefits to predictive maintenance and business. Methodology/approach: A literature review was carried out followed by a case study Originality/Relevance: Focusing the development of maintenance techniques, especially predictive maintenance and those supported by enabling technologies from Industry 4.0, such as Internet of Things (IoT), it may be possible to carry out online monitoring of spindles with a focus on reducing catastrophic or unplanned events. Main results: The main results are to know the normal behavior of the machine, the possibility of obtaining information in real time, managerial data for sight management, and the possibility of identifying spindle failure before it becomes a catastrophic failure, thus reducing the costs of maintaining the spindles. Theoretical contributions: As a contribution, we discuss the development of the system to digitize the data through the operation available in an outsourced cloud environment. This data can then be returned to the company in the form of dashboards for cash management, developing agility in decision making to facilitate the predictive maintenance in addition to validating the online monitoring system for spindle management in furniture industry processes

Industry 4.0 in maintenance: Using condition monitoring in electric machines

Industry traditionally considered maintenance as a cost and a necessity to replace equipment and machines, but the path has changed to better focus on maintenance to prevent faults and it was designated as predictive. The ones motivated to take these advantages are faced with two of the biggest barriers: the investment it requires and the difficulty to develop algorithms. The costs of installation are still high, but the avoided costs surpass it. Also, Internet of Things (IoT) has brought a big shift, which is been known as the industry 4.0. One of the potentials in maintenance is the conditioning monitoring. Condition monitoring sensors and devices are now linked to maintenance platforms, providing real-time data. This new connectivity is both more affordable and easier to implement than predictive maintenance. Real-time data allows managers to adjust preventive maintenance plans while providing greater reliability. At the same time, artificial intelligence manages this data to recognize patterns, which is one of the most promising advances in digital reliability. So, regardless of the ability to immediately implement a preventive maintenance plan, condition monitoring is an asset itself. The present paper presents the common faults on electric machines, their effects, their impact on the industry and the main techniques on condition control to prevent them. It is also added the reflection on the use of IoT to enhance the potential of condition control maintenance. The implementation of continuous improvement actions throughout the life of the equipment allows to increase efficiency, either by overcoming weaknesses or by adapting production or operational capacities to processes, production or maintenance, avoiding under maintenance or over maintenance and minimizing operating costs.info:eu-repo/semantics/publishedVersio

Dental manifestations in bariatric patients: review of literature

The rate of bariatric surgery has significantly risen in the past decade as an increasing prevalence of extreme obesity can be observed. Although bariatric surgery is an effective therapeutic modality for extreme obesity, it is associated with risk factors affecting also oral health. Based on an overview of the current literature, this paper presents a summary of dental manifestations in bariatric patients. Bariatric surgeries are associated with an increased risk for gastro-esophageal reflux which in turn might account for the higher amount of carious and erosive lesions observed in bariatric patients. As a result, also dentin hypersensitivity might be observed more frequently. The current data indicate that recommended postsurgical meal patterns and gastric reflux might increase the risk for dental lesions, particularly in the presence of other risk factors, such as consumption of sweet-tasting foods and acidic beverages. Further research is needed to evaluate the correlation of bariatric surgery and the development of dental diseases