Software Maintenance Management Research Articles

Esign and development of preventive, corrective and predictive maintenance manager software

Due to the need to have adequate and affordable software for maintenance management, at the Universidad Tecnológica de Oriental, a preventive, corrective and predictive maintenance management software was designed and developed, the needs of organizations have been analyzed and considered. in terms of maintenance management, designing a conceptual architecture that integrates the maintenance modalities and ensures the modularity and scalability of the software. In addition, key functionalities were validated and early feedback from users was obtained, allowing continuous improvements in successive iterations. The software offers efficiency, productivity, economic gains, production improvements and loss reduction. Thus, the development of maintenance management software meets the needs of organizations, improves maintenance management, reduces costs and promotes a culture of continuous improvement.

Clinical Equipment as a Potential Impediment to Optimal Intrapartum Monitoring and Delivery for Pregnant Women in South Africa

Clinical equipment is essential in a labour unit to assess, monitor, diagnose, and prevent complications during labour. The availability of good working equipment in the labour unit is needed to enhance optimal intrapartum monitoring and delivery for pregnant women. Thus, this paper employed a cross-sectional descriptive design using a quantitative research approach to ascertain how equipment impedes optimal intrapartum monitoring and delivery for pregnant women. A total of 59 midwives were recruited to participate in the study. Data collected using an electronic structured questionnaire were analysed with descriptive statistics using Statistical Package for Social Sciences (SPSS) version 25.0. The study reported that most midwives (68%) in labour units experienced barriers to using equipment when administering care to pregnant women. The barriers were perpetuated by various factors, such as bed capacity, in meeting patient demands, including examination lights, overhead radiant warmers, and examination weighing scales for newborns. Incorporating mandatory computerized maintenance management software is recommended to improve the quality of maternity equipment. In addition, there is a need for regular equipment inspections and maintenance by skilled technicians in selected hospitals of Limpopo Province, South Africa.

Improving Cultural Heritage conservation: LSTM neural networks to effectively processing end-user’s maintenance requests

Preventive conservation of cultural heritage can avoid or minimize future damage, deterioration, loss and consequently, any invasive intervention. Recently, Machine Learning methods were proposed to support preventive conservation and maintenance plans, based on their ability to predict the future state of the built heritage by collected data. Several data sources were used, such as structural data and images depicting the evolution of the deterioration state, but till now textual information, exchanged by people living or working in historical buildings to require maintenance interventions, was not used to support conservation programmes. This work proposes a method to support preventive conservation programs based on the analysis of data collected into CMMS (computer maintenance management software). In a Cultural Heritage building in Italy, hosting a University Campus, data about end-user’s maintenance requests collected for 34 months were analysed, and LSTM neural networks were trained to predict the category of each request. Results show a prediction accuracy of 96.6%, thus demonstrating the potentialities of this approach in dynamically adapting the maintenance program to emerging issues.

Improving Cultural Heritage conservation: LSTM neural networks to effectively processing end-user’s maintenance requests

Preventive conservation of cultural heritage can avoid or minimize future damage, deterioration, loss and consequently, any invasive intervention. Recently, Machine Learning methods were proposed to support preventive conservation and maintenance plans, based on their ability to predict the future state of the built heritage by collected data. Several data sources were used, such as structural data and images depicting the evolution of the deterioration state, but till now textual information, exchanged by people living or working in historical buildings to require maintenance interventions, was not used to support conservation programmes. This work proposes a method to support preventive conservation programs based on the analysis of data collected into CMMS (computer maintenance management software). In a Cultural Heritage building in Italy, hosting a University Campus, data about end-user’s maintenance requests collected for 34 months were analysed, and LSTM neural networks were trained to predict the category of each request. Results show a prediction accuracy of 96.6%, thus demonstrating the potentialities of this approach in dynamically adapting the maintenance program to emerging issues.

Current Practices for Preventive Maintenance and Expectations for Predictive Maintenance in East-Canadian Mines

Preventive maintenance practices have been proven to reduce maintenance costs in many industries. In the mining industry, preventive maintenance is the main form of maintenance, especially for mobile equipment. With the increase of sensor data and the installation of wireless infrastructure within underground mines, predictive maintenance practices are beginning to be applied to the mining equipment maintenance process. However, for the transition from preventive to predictive maintenance to succeed, researchers must first understand the maintenance process implemented in mines. In this paper, we conducted interviews with 15 maintenance experts from 7 mining sites (6 gold, 1 diamond) across East-Canada to investigate the maintenance planning process currently implemented in Canadian mines. We documented experts’ feedback on the process, their expectations regarding the introduction of predictive maintenance in mining, and the usability of existing computerized maintenance management software (CMMS). From our results, we compiled a summary of actual maintenance practices and showed how they differ from theoretical practices. Finally, we list the Key Performance Indicators (KPIs) relevant for maintenance planning and user requirements to improve the usability of CMMS.

SOFTWARE MAINTENANCE MANAGEMENT IN MICRO SOFTWARE COMPANIES

Software maintenance is one of the main processes in software companies. It is regarded as more complex and costly compared to software development, and therefore should be carefully planned and managed. Micro software companies are companies with up to 10 employees, and they represent a significant driver of economic development in many countries around the world. However, micro companies have specific internal organizations and a business model, but also have significant constraints on human and financial resources. After outlining the basic concepts of software maintenance and the characteristics of small and micro software companies, the paper presents the author’s experience in software maintenance management in a local micro software company in Serbia. Maintenance management was implemented through a project aimed at improving maintenance processes in the company. The main objective was the improvement of maintenance request processing, which resulted in the implementation of a technical solution related to the timeline of maintenance requests. Since the process improvement project fosters organizational learning and knowledge management activities, a knowledge identification and systematization project was implemented as a subproject. Presented experience gained through fieldwork in the company contributed to the overall knowledge base about software engineering practice in micro software companies, which can be beneficial to both researchers from academia and practitioners from industry.

Maintenance Management and Organizational Performance in Selected Manufacturing Firms, Akwa Ibom State

This research was designed to examine the relationship between Maintenance Management and organizational performance among selected manufacturing firms in Akwa Ibom State. Survey research design was adopted for the study and a sample size of 258 respondents was drawn from the population of 275. For the objective of the study to be achieved, five hypotheses were formulated. The major instrument for data collection was a structured questionnaire administered to the respondent using random sampling techniques. Data collected were analysed using simple percentage and Ordinal Logistic Regression. Results show that there is a significant correlation between variables of maintenance management such as corrective, preventive, condition-based maintenance and pre-determined maintenance and organizational performance variables of effectiveness, efficiency and profitability among selected manufacturing firms in Akwa Ibom State. Based on the finding of the analysis, management has to provide the maintenance teams with a maintenance management software in order to ensure proper interventions monitoring as well as smooth communication between technicians and other professionals to enhances business success. Consequently, it is recommended that Management should ensure that Corrective maintenance is implemented right after a defect has been detected on a piece of equipment or a production line: its objective is to make the piece of equipment work normally again, so that it can perform its assigned function. Corrective maintenance can either be planned or unplanned depending on whether or not a maintenance plan has been created.

Maintenance Management and Organizational Performance in Selected Manufacturing Firms, Akwa Ibom State

This research was designed to examine the relationship between Maintenance Management and organizational performance among selected manufacturing firms in Akwa Ibom State. Survey research design was adopted for the study and a sample size of 258 respondents was drawn from the population of 275. For the objective of the study to be achieved, five hypotheses were formulated. The major instrument for data collection was a structured questionnaire administered to the respondent using random sampling techniques. Data collected were analysed using simple percentage and Ordinal Logistic Regression. Results show that there is a significant correlation between variables of maintenance management such as corrective, preventive, condition-based maintenance and pre-determined maintenance and organizational performance variables of effectiveness, efficiency and profitability among selected manufacturing firms in Akwa Ibom State. Based on the finding of the analysis, management has to provide the maintenance teams with a maintenance management software in order to ensure proper interventions monitoring as well as smooth communication between technicians and other professionals to enhances business success. Consequently, it is recommended that Management should ensure that Corrective maintenance is implemented right after a defect has been detected on a piece of equipment or a production line: its objective is to make the piece of equipment work normally again, so that it can perform its assigned function. Corrective maintenance can either be planned or unplanned depending on whether or not a maintenance plan has been created.

An IoT-based maintenance framework for irrigation and drainage water management system at regional scale

The management of the geographically distributed assets of irrigation and drainage water grids compels a challenging alignment of operations like maintenance plans, resource allocation, and spare parts inventory management systems. We propose an IoT-based maintenance framework to optimize reliability, management costs, and logistics and increase the resilience and sustainability of the irrigation and water management network. The proposed framework provides an interface between the centralized inventory system and the maintenance and logistics operations carried out throughout the network. Information exchange is supported by bar code and RFID technologies integrated within the IT system of the company. A Maintenance Management Software (MMS) able to store assets' physical hierarchy data and inventory data is the supporting tool that fuels the framework. The framework is applied to a regional drainage water system in the Emilia-Romagna region (Italy), improving the visibility of the infrastructural network and enabling tailored and data-driven preventive maintenance plans. The combination of the components' availability, logistics and maintenance costs, failure trend, and impact on the overall network contribute to establishing new methods for assessing the threshold of service level (i.e., reliability) to guarantee for each material.

Evaluation of the use of a specially designed saw to remove penis rings at the emergency department.

Objective:Penile strangulation is a rising problem in emergency departments (ED) and can cause serious medical issues. The removal of a penile ring requires immediate action, but is a difficult task. In this study an in-house specialised designed saw to safely remove penis rings is evaluated.Materials and Methods:To evaluate the use of the penis ring saw we used information from our maintenance management software to evaluate the amount of malfunctions. The evaluation of the experiences in the ED were based on semi-structured interviews with ED employees and with the mechanical engineers that developed and maintain the saw.Results:Since 2013 seven jobs were found regarding to a defect of the saw. All defects were broken saw blades. Four emergency care department employees and two instrumentmakers were interviewed. All four are pleased with the saw, because it improves patient safety during removal of the penis ring. The two instrument makers agree with the ED nurses that the saw is an improvement compared to the previous used solutions. Possible improvements were also suggested.Conclusion:A specialized saw was designed and developed for the removal of penis rings. This saw offers a safe and standardized way to remove the penis rings.

Design of Automobile Rapid Maintenance Based on Digital Maintenance Assistant System

In recent years, with the rapid growth of China’s automobile ownership, the profit proportion of automobile aftermarket in the automobile industry is increasing day by day, and the automobile service industry is gradually growing in the development of China’s national economy. The current automobile maintenance management software is not good and bad, most of these management software in order to meet the common possible user needs and lead to the same software function, lack of consideration for the management system of small and medium-sized enterprises, and there are certain defects in generality. At the recent 2020 China Automobile Supply Chain Conference, Wu Wei, director of the Machinery Department of the Industrial Development Department of the national development and Reform Commission, said that the production and sales volume of the automobile market had achieved a year-on-year growth for six consecutive months. If this momentum can continue in the fourth quarter, the total production and sales volume by the end of this year is expected to be close to the level of last year. Automobile fast repair refers to the activities of automobile maintenance and minor repair, but not vehicle repair, automobile assembly repair and secondary maintenance. The service scope is locked in 120 fast repair and maintenance items that can be completed within 2 hours. At present, the total number of motor vehicles in our country is huge, and the number of maintenance enterprises can not meet the demand of maintenance, so the potential of automobile fast repair market is unlimited. As the main business of fast repair industry, automobile fast repair is paid more and more attention by people. The application of digital management mode and maintenance cases creates good conditions for the development of fast repair enterprises, and makes it possible for fast repair enterprises to adopt reasonable maintenance methods. This paper focuses on the chaos in maintenance management, On the basis of the research and analysis of automobile maintenance management system and digital management concept, taking customer demand as the starting point, this paper designs a digital automobile maintenance auxiliary system specially for automobile fast repair enterprises to assist managers in maintenance management, so as to achieve the purpose of standardized management business “fast and reasonable” maintenance, and improve customer satisfaction.

Optimize the maintenance activity with computer application

The paper contains a few knowledges about the maintenance activity to establish an optimal maintenance strategy with computer application. Maintenance activity is theoretically analyzed by finding a logical scheme for implementing a maintenance strategy and a brief description of the advantages of implementation a computerized maintenance management software.

АРХИТЕКТУРА ПРОГРАММНОГО КОМПЛЕКСА УПРАВЛЕНИЯ РЕМОНТАМИ И ТЕХНИЧЕСКИМ ОБСЛУЖИВАНИЕМ ДЛЯ СЕРВИСНОГО ПРЕДПРИЯТИЯ

The paper provides an overview of the architectures for the repair and maintenance management software package for a service enterprise. As part of the research work, asset management (EAM) and service management (ITSM) methodologies were studied. Three different architectures for the designed software package are proposed, their descriptions, advantages and disadvantages are given.

Effect of applying lean maintenance in oil and gas fields

Oil and Gas Sector are facing a huge increase and delay in Operations & Maintenance tasks for all facilities beside continuous demand from management to improve the productivity of wells and the efficiency of facilities. The top management decides to use Lean Maintenance as a new tool, technique and methodology to improve and modify the current operations, production and maintenance systems as done before by many researchers in the oil and gas sector. This improvement will be done through three real case studies by integrating Building Information Modelling with lean concepts, monitoring Key Performance Indicators within a modern Computerized Maintenance Management Software and finally using some LM tools such as Total Productive Maintenance, Value Stream Mapping and 5S Methodology to increase productivity, efficiency, and quality of the output production and services. The results of implementation since July 2017 till June 2018 show average increase in crude oil production by 6.72% per day in addition to overcome natural decline of oil wells, reduced Technician’s total Preventive Maintenance tasks by 52.63% and transfer the less difficult inspections to Operator to be responsible for making checks to all parameters of all equipment and to enable Technicians to perform other maintenance tasks, Saving about $724,770 in Water Injection Pumps Operation’s Expense. Last but not least, accelerate the workflow of production and maintenance processes by 28% compared with the previous financial year.

Application of 4G IOT Card in Automatic Weather Station

The “Industry Application Card” (an SIM card of the 2G dedicated line network) for the automatic transmission of weather station data widely used by the meteorological department of Liaoning Province had been strictly investigated, and it was found that the “Industry Application Card” supports the access between the public network and the private network, and allows text messages to be sent to the “civil SIM card” of the public network through the private network, so it is the preferred SIM card for telecom fraudsters. The 4G IoT card solves these problems. Open the Ping Tester app after inserting the IoT SIM card into the tester mobile, then use it to ping the IP address of the server in Liaoning Meteorological Information Center. A successful connection would imply that the connection to the Liaoning Meteorological Information Center’s Intranet via IoT is functional, and that the IoT SIM card can be used to automatically transmit the meteorological station’s data. The automatic weather stations generally using the automatic weather station models of local meteorological bureaus in Liaoning Province can use “Huayun Shangtong local maintenance management software” for the parameters configuration of automatic weather stations. After the “Huayun Shangtong local maintenance management software” is connected to the port of the automatic weather station, by finding the matched automatic weather station type, entering the error diagnosis interface of the corresponding station type, clicking the “Start Monitoring” button to read the device status information.

An open-source automated continuous condition-based maintenance platform for commercial buildings

Many studies have documented that retro-commissioning provides energy savings ranging between 10 and 30%; in some cases, more than 50% of a building's energy consumption. Over the past two decades, retro-commissioning has evolved from being mostly a manual process to using functional testing to a semi-automated process of using monitored data to identify operational problems. Many of the issues that the retro-commissioning process identifies relate to the inability to manage and maintain building systems and controls associated with those systems. Even though retro-commissioning has proven to be cost-effective, only a small fraction of the buildings are commissioned and many buildings that are commissioned only implement a fraction of recommend retro-commissioning actions. Two primary reasons for lack of interest in retro-commissioning is a perception that: (1) retro-commissioning is expensive and (2) many retro-commissioning measures lack persistence. Many cities in the United States are mandating that some of the commercial building stock be commissioned periodically. Automation and leveraging emerging building information modeling standards can alleviate many of the concerns of retro-commissioning by providing a mechanism for automated continuous condition-based maintenance. This article describes one such reference process that can be deployed to provide continuous automated condition-based maintenance management for buildings that have building information modeling, building automation systems, and computerized maintenance management software systems. The process can be deployed using an open-source transactional network platform, VOLTTRON™, designed for distributed sensing and controls and supports both energy efficiency and grid services.

Technology adoption: A study on post-implementation perceptions and acceptance of computerised maintenance management systems

Information and communications systems are increasingly being used to capture, record, store, transmit and retrieve data to manage the maintenance of equipment and physical infrastructure. The justification for the costs incurred in implementing computerised information systems subsumes that acceptance of the associated technology by the users will provide the desired future benefits to the business organisation. The study assumes that the respective organisations were ready for the implied change, and thus applied the premise that perception influences acceptance to assess the implementation of computerised maintenance management software systems in a number of user organisations. Respondents to the study indicated that ease of use, usefulness and system characteristics were strongly dependent on the level of training of the user during the implementation of the computerised maintenance management software system, thus reiterating that user training influences perception which, in turn, influences user acceptance of technology. A model to predict user perception is developed based on data arising from respondent feedback.

Three empirical studies on predicting software maintainability using ensemble methods

More accurate prediction of software maintenance effort contributes to better management and control of software maintenance. Several research studies have recently investigated the use of computational intelligence models for software maintainability prediction. The performance of these models, however, may vary from dataset to dataset. Consequently, ensemble methods have become increasingly popular as they take advantage of the capabilities of their constituent computational intelligence models toward a dataset to come up with more accurate or at least competitive prediction accuracy compared to individual models. This paper investigates and empirically evaluates different homogenous and heterogeneous ensemble methods in predicting software maintenance effort and change proneness. Three major empirical studies were designed and conducted taken into consideration different design such as the types of the investigated ensembles methods, types of prediction problems, used datasets, and other experimental setup. Overall empirical evidence obtained from the three studies confirms that some ensemble methods provide more accurate or at least competitive prediction accuracy compared to individual models across datasets, and thus they are more reliable.

Third-Party Application Maintenance Management

The success and failure of software projects are based on performance indicators such as: compliance to the customer first requirements, customer satisfaction, software quality, budget overrun, schedule compliance and so on. Certainly, project management approaches and best practices known in the field of software engineering or others have been used in software maintenance (SM) management to better position these performance indicators and therefore promote project success. This paper concerns especially Third-party Application Maintenance (TPM). It presents and discusses the few approaches proposed in the literature that have been able to meet the challenges of this software engineering area under specific conditions and in an outsourcing context.

Software architecture knowledge for intelligent light maintenance

The maintenance management plays an important role in the monitoring of business activities. It ensures a certain level of services in industrial systems by improving the ability to function in accordance with prescribed procedures. This has a decisive impact on the performance of these systems in terms of operational efficiency, reliability and associated intervention costs. To support the maintenance processes of a wide range of industrial services, a knowledge-based component is useful to perform the intelligent monitoring. In this context we propose a generic model for supporting and generating industrial lights maintenance processes. The modeled intelligent approach involves information structuring and knowledge sharing in the industrial setting and the implementation of specialized maintenance management software in the target information system. As a first step we defined computerized procedures from the conceptual structure of industrial data to ensure their interoperability and effective use of information and communication technologies in the software dedicated to the management of maintenance (E-candela). The second step is the implementation of this software architecture with specification of business rules, especially by organizing taxonomical information of the lighting systems, and applying intelligence-based operations and analysis to capitalize knowledge from maintenance experiences. Finally, the third step is the deployment of the software with contextual adaptation of the user interface to allow the management of operations, editions of the balance sheets and real-time location obtained through geolocation data. In practice, these computational intelligence-based modes of reasoning involve an engineering framework that facilitates the continuous improvement of a comprehensive maintenance regime.