Service Engineering Research Articles

Studies on Performance Deterioration of a Low Bypass Turbofan Engine in Service

The performance deterioration of a low bypass turbofan engine is analyzed to find out its causes. The performance parameters are compared with their limitations for a specific throttle setting. Dirt buildup, soot deposit, de-twisting of turbine blades, malfunction of atomizers and fuel system accessories are found to degrade the engine health and performance before the intended service period. Periodic compressor wash and engine maintenance, cleaning or replacement of fuel filters and good assembly practices are found beneficial in addressing the issues and retaining the engine performance.

Design of Waste Tyre Flexible Couplings for Generating Plant

There is a growing need at creating wealth from wastes. Waste tyres have been littering our environment. There is need to create ways of utilizing them effectively after their critical mechanical properties have been investigated. Flexible couplings made of waste tyres were designed using power ratings and service factors of generating plant. Coupling sizes, dimensions, among other physical properties were selected at varying Internal Combustion Engine (ICE) speeds; 1000, 2000 and 3000 rpm, from which the choices of waste tyre couplings were made. The results of over 16 hours of running of the generating plant using coupling size F 60 selected based on service factor (1.5), engine speed (1000 rpm), bore diameters ( 42-48 mm) and power rating (11.10 kW) performed satisfactorily. Therefore, the waste tyre flexible couplings are capable of transmitting power/torque from the generating plant without failure within the test hours.

MODULAR MAINTENANCE DECISION ARCHITECTURE

AbstractThe operation of large production assets requires many decisions from the acquisition and design of new assets to the choice of lubricant for a specific piece of equipment. The decisions made in maintenance have a direct effect on the management of the production process, making it important to ensure correct maintenance decision making. However, studies on maintenance decision making tend to focus on smaller areas of decisions being made in a process, but rarely the entire process. To introduce more studies that consider the entire maintenance process, this paper proposes using a modular Maintenance Decision Architecture. The paper introduces a framework for structuring information sources into standardized information modules and mapping them to maintenance decisions made across the entire organization. The application of approaches from product, system, and service engineering are used to support the management of the complexities of maintenance of large production facilities.

BIMBINGAN TEKNIS TENAGA KERJA KONSTRUKSI UNTUK PENGAWASAN BANGUNAN GEDUNG DAN MANDOR KONSTRUKSI

The building is one of the human needs and is used as a place to live and do other activities, it consists of a combination of several materials and constructions to function as planned. Construction is part or all of the activities that include building construction, demolition, operation, and maintenance. One of the most essential processes in construction work is the issue of supervising construction work. As a unit in construction work, the supervisory position has two functions: monitoring and managerial. The training methods implemented in this activity are lecture, presentation, assignment, and discussion methods. Based on this, the Ministry of Public Works and Public Housing, Director General of Construction Development for Region VII Jayapura, collaborated with the Southeast Maluku Regency PUPR Service and Civil Engineering Study Program to carry out Bimtek activities with 32 participants. What was achieved in this activity by the participants was an increase in the knowledge and skills of supervision and construction work processes where the presenters found a significant increase in the participants when compared to the initial meeting

Measuring quality perception of public services: customer-oriented approach

Abstract The focus of this research is on assessing the perception of public service quality through a customer-centred approach. Public service quality comprises multiple factors that are prioritised differently by customers. Therefore, the study aims to conduct a literature review to identify the primary quality dimensions of public services and evaluate the heterogeneity of their perception within the context of Lithuania. The research measures the user perceptions of public service quality. The literature review allowed for identifying service quality indicators and grouping them into dimensions based on unifying characteristics. Such identification of service quality dimensions grounded the research methodology. An adapted SERVQUAL model was used to analyse data collected by a survey to interview customers of Lithuanian public service organisations. Logit and probit models were applied to examine the effect of socio-demographic characteristics and the type of service on customer perceptions of different quality aspects of the provided public services. Explored heterogeneity of attitudes and detailed analysis of socio-demographic factors revealed that women with higher education are the most satisfied users of public services, while less educated men usually have a negative attitude towards the quality of public services. The study confirmed that marital status and income level are not related to customer satisfaction with service quality. Although gender, age, family size, education level, and employment status explain heterogeneity in customer satisfaction, they still account for only a small amount of variance compared to the place of residence and type of service. The study is a significant contribution to the field of service engineering as it introduces a systematic approach to the development of service quality, incorporating models and methods that enable the assessment of service quality and efficiency. The literature review has identified several research gaps related to public service quality, including a lack of research on general public services and areas such as tourism, real estate management, fire protection and rescue.

Joint scheduling of spare parts production and service engineers based on progressive Pareto algorithm

ABSTRACT We analyse the joint scheduling of spare parts production and service engineers in a multi-site maintenance system. In the system, for each failure, a service engineer with the required spare part needs to be allocated for on-site maintenance. If one of the required resources is not readily available, the maintenance task can be satisfied via an external channel with quick responsiveness but high involved costs. Service providers need to make an efficient plan, including production scheduling of spare parts, allocation of service engineers and outsourcing strategy. First, a mathematical model with the objectives of minimum total outsourcing costs and minimum weighted tardiness is formulated. Then, a novel and knowledge-based heuristic algorithm is developed, namely progressive Pareto algorithm based on step-size (PPAS). To verify the performance of PPAS, it is compared against other well-known algorithms, including NSGA-II, MOEA/D, NNIA, RIPG, MMOIG and MNNIA. Finally, the effectiveness of the joint scheduling mode is demonstrated by comparing it with the separate optimisation mode of spare parts production and workforce allocation. Highlights Analyse the joint scheduling of spare parts production and service engineers Construct a bi-objective optimisation model Develop a progressive Pareto algorithm based on step-size Verify the superiority of the proposed algorithm and joint scheduling mode

Two-stage multi-step energy model calibration of the cooling systems of a large-space commercial building

Buildings play a major role in energy expenditure, representing 40% of Europe’s total energy consumption. It is estimated that heating, ventilation, and air conditioning systems consume between 50–60% of the total energy spent inside the building, thus corresponding to 20% of global worldwide energy consumption. Hence, there is a need to improve the accuracy of building thermal simulation and energy models that are essential in regulatory compliance calculations. In the present study, the authors empirically validate an optimization-based calibration methodology based on its application to a fully operational commercial building located in Pamplona, Navarre. The methodology used a white-box two-stage model in EnergyPlus, which combines a load profile object and a district cooling component to distribute the cooling load inside the building’s thermal zones. The study optimized the parameters and performance curves of different cooling system components using a second-generation non-sorting genetic algorithm in jEPlus software and 985 h of ten-minute time-step data. Finally, a multi-level benchmark is executed, which evaluates the electric energy consumption of the building’s heat pumps and the interior temperature of the different thermal zones for summer 2020 conditions. The assessment of the thermal and energy performance of the simulation model was conducted according to the requirements of the American Society of Heating, Refrigerating and Air-Conditioning Engineers, Guideline 14-2002, and the Chartered Institution of Building Services Engineers, Operation Performance Technical Memoranda 63.

Introducing digital technologies in person-related services—Support through Social Service Engineering

The trend towards digitalization has made its way into personal services, promising better service quality for customers and improved working conditions for service providers. However, the implementation of digital technologies remains a major challenge, especially for smaller companies. Building on the results of the SO-SERVE project, this paper presents the concept of Social Service Engineering and its practical application in introducing a digital tool in two daycare centers. The software provided to the employees on tablets was intended to support the information and documentation processes, as the design of internal and external information flows and documentation processes in the daycare centers proved to be particularly challenging. The paper presents two exemplary SO-SERVE tools used in the daycare centers: ‘Digitization Checklists’ provide company managers and business unit managers with an overview of the necessary steps for the standardized use of software and hardware within the company. ‘Digitization companions’ are employees who are readily available to their colleagues as contact persons for questions and concerns about working with the new digital tool. An initial online evaluation with 23 educators from the daycare centers reveals that the digital tool and supporting SO-SERVE tools have improved information and documentation processes, and the work situation of employees. Both educators and parents benefit from the improvements.

Randomized Error Removal for Online Spread Estimation in High-Speed Networks

Flow spread measurement provides fundamental statistics that can help network operators better understand flow characteristics and traffic patterns with applications in traffic engineering, cybersecurity and quality of service. Past decades have witnessed tremendous performance improvement for single-flow spread estimation. However, when dealing with numerous flows in a packet stream, it remains a significant challenge to measure per-flow spread accurately while reducing memory footprint. The goal of this paper is to introduce new multi-flow spread estimation designs that incur much smaller processing overhead and query overhead than the state of the art, yet achieves significant accuracy improvement in spread estimation. We formally analyze the performance of these new designs. We implement them in both hardware and software, and use real-world data traces to evaluate their performance in comparison with the state of the art. The experimental results show that our best sketch significantly improves over the best existing work in terms of estimation accuracy, packet processing throughput, and online query throughput.

Perspectives of using artificial intelligence elements in bread baking

Enterprises of bread baking sector produce traditional everyday products and, at the same time, this sector remains one of the most conservative ones. There are always new types of raw materials and additives on the market, but new recipes are developed traditionally based on the results of test baking. However, a technologically justified solution is not always optimal regarding nutritional value. The purpose of this work is consideration of the possibilities and prospects of using elements of artificial intelligence (AI) in bread baking based on examples from other sectors of the food industry and study the AI’s ability to analyze and evaluate (categorise) existing recipes of bread products. The initial stage of AI use is machine learning (ML), but today there are no unified electronic databases that can be used to fulfil the task. We took approved collections of recipes as the basis for filling such databases. In addition, technologically acceptable variations of the main recipe components and their mutual substitution were carried out. The base was analyzed using Microsoft Azure Machine Learning service and Google Cloud Machine Learning Engine. Normalised database with 5,000 variants of recipes of bakery products that can be manufactured in conditions of both large industrial companies and small bakeries were created. The ML showed that the system effectively determines the main components of recipes and can independently, with high accuracy, classify recipes entered by the user into categories "bread" or "enriched bread". The work showed the possibility and viability of using AI elements in the baking industry. The database can be used to design new bakery products with specified recipe composition and (after improvement) to model applications with specified chemical composition or biological value.

Cases Integration System for Fault Diagnosis of CNC Machine Tools Based on Knowledge Graph

Due to the time-consuming and labor-consuming maintenance required by appealing to service engineers during the diagnosis of CNC machine tool faults, the CNC machine tool fault diagnosis system has become the economical practical choice of intelligent workshop now, which can help CNC machine tool operators quickly locate and eliminate faults. Knowledge graph technology plays a great role in the use of structured data, and has also achieved a certain degree of research progress and good applications in other professional fields. This article focuses on how to extract semi-structured and unstructured fault knowledge from the abundant CNC machine tool fault cases, fault repair manuals and on-site maintenance logs on the market. A complete system is used to integrate this fault diagnosis knowledge with different formats and content but interrelated, so as to realize the structured application of fault diagnosis knowledge of CNC machine tools. This paper first fully analyzes the content and structural characteristics of these fault cases, and optimizes the design of a set of domain ontology for machine tool fault diagnosis, which contains 8 types of ontoly and 7 types of relation. Using the rule-based knowledge extraction method combined with the BiLSTM-CRF information extraction algorithm to extract effective information from this knowledge. Finally, the structured knowledge is stored through the Neo4J graph database for visualization. Under the application of a good ontology, the accuracy and effectiveness of the composite extraction algorithm have been proved to be greatly improved compared with the single information extraction algorithm in the experimental verification process.

A Virtual Reality Lab for Automotive Service Specialists: A Knowledge Transfer System in the Digital Age

Under the influence of the COVID-19 pandemic, there is an accelerated transition from the traditional form of knowledge transfer to online learning. Our study of 344 automotive students showed that the success of this transition depends on the readiness to introduce special digital tools for organizing knowledge and conducting practical forms of classes. In this regard, a modern digital form of organizing and transferring knowledge to automotive service engineers in the form of virtual laboratories was developed and presented in the article. The work scenarios, functionality, and minimum technical requirements of virtual laboratories as software systems are described and reviewed in the paper. The rationale for the effectiveness of the application, based on the results of using 109 university students in training practice, is presented as a result of the research. An analysis of the distributions of the student survey results and their training progress revealed differences at the p = 0.05 significance level. This confirmed the hypothesis that the use of methods for teaching engineers special disciplines and language skills using VR technologies is much more effective than the traditional one. An increase in students’ interest in learning was revealed, and their performance improved markedly. This proves that the immersive nature of VR technology makes it possible to better assimilate the studied material, increase the level of motivation of future car service specialists, and also allow the organization of the transfer of knowledge online. The very process of knowledge transfer becomes the point of acquiring new digital competencies necessary for high-tech industries.

Towards a cognitive engineering of transactional services in IoT based systems

Cognitive computing is the capability of a system to mimic the ability of human brain to learn and adapt from the surroundings. Cognitive systems have decision-making capabilities based on new information, actions and outcomes. Similarly, Internet of Things (IoT) aims at making things smart, and enabling them to perform complex tasks. Reliability and flexibility are persistent challenges in the IoT context where the promise is managing a multitude of devices and delivering real-time responses for critical smart applications. A limited number of studies examine these challenges while considering cognitive capabilities of things and have failed to handle thing’s specificities in terms of communication bandwidth, power availability and storage capacity. Following the service oriented architecture (SOA), the functionality can be encapsulated as services. Thus, automating the management of transactional services in smart IoT ecosystem can be fulfilled through the coupling of transactional properties to cognitive things. This paper provides a comprehensive approach to alleviate reliability restrictions in cognitive IoT service compositions. The concept of cognitive faculty (CF) is introduced to leverage transactional properties of services and can be customized to specific requirements of IoT applications. A proof-of-concept is included in this paper based on a self-monitoring IoT application for diabetic patients.

Approach for determining the availability of machine tools based on skill level of operator and service personnel

Machine tools (MTs) availability is a critical measure for production scheduling. On the other hand, the machine tool availability depends on its reliability (mean time between failure, MTBF) and maintainability (mean time to repair, MTTR), which depends on multiple factors and uncertainties. One can consider the skill level of operators and service personnel that influence MTBF and MTTR of machine tools, which in turn can affect operating cost. The studies on the effect of the skill level of operators and service personnel on MT availability are limited. Generally, MT availability should be higher to maintain reasonable operating costs. In the current work, a multi-objective optimization (MOO) problem was formulated to maximize the MT availability and minimize the MT life cycle cost, considering the skill levels of the MT operators and service personnel. The results of this study help the management identify the skill level of operators and service engineers for maximum MT availability.

Enhancement of Heavy-Duty Engines Performance and Reliability Using Cylinder Pressure Information

Sustainability issues are becoming increasingly prominent in applications requiring the use of heavy-duty engines. Therefore, it is important to cut the emissions and costs of such engines to reduce the carbon footprint and keep the operating expenses under control. Even if for some applications a battery electric equipment is introduced, the diesel-equipped machinery is still popular thanks to the longer operating range. In this field, the open pit mines are a good example. In fact, the Total Cost of Ownership (TCO) of the mining equipment is highly impacted by fuel consumption (engine efficiency) and reliability (service interval and engine life). The present work is focused on efficiency enhancements achievable through the application of a combustion control strategy based on the in-cylinder pressure information. The benefits are mainly due to two factors. First, the negative effects of injectors aging can be compensated. Second, cylindrical online calibration of the control parameters enables the combustion system optimization. The article is divided into two parts. The first part describes the toolchain that is designed for the real-time application of the combustion control system, while the second part concerns the algorithm that would be implemented on the Engine Control Unit (ECU) to leverage the in-cylinder pressure information. The assessment of the potential benefits and feasibility of the combustion control algorithm is carried out in a Software in the Loop (SiL) environment, simulating both the developed control strategy and the engine behavior (Liebherr D98). Our goal is to validate the control algorithm through SiL simulations. The results of the validation process demonstrate the effectiveness of the control strategy: firstly, cylinder disparity on IMEP (+/−2.5% in reference conditions) is virtually canceled. Secondly, MFB50 is individually optimized, equalizing Pmax among the cylinders (+/−4% for the standard calibration) without exceeding the reliability threshold. In addition to this, BSFC is reduced by 1% thanks to the accurate cylinder-by-cylinder calibration. Finally, aging effects or fuel variations can be implicitly compensated, keeping optimal performance thorough the engine life.

Developing Reliable Digital Healthcare Service Using Semi-Quantitative Functional Resonance Analysis

Since entering the era of Industry 4.0, the concept of Healthcare 4.0 has also been put forward and explored by researchers. How to use Information Technology (IT) to better serve people’s healthcare is one of the most featured emerging directions in the academic circle. An important field of Healthcare 4.0 research is the reliability engineering of healthcare service. Because healthcare systems often affect the health and even life of their users, developers must be very cautious in the design, development, and operation of these healthcare systems and services. The problems to be solved include the reliability of business process, system functions, and personal healthcare data. The Functional Resonance Analysis Method (FRAM) has been applied in reliability engineering for safety-critical systems in available studies, using both qualitative and quantitative approaches. However, the method has not been applied in the field of digital healthcare services development. Therefore, to narrow the gap, we present in this paper a semi-quantitative functional resonance analysis method to develop reliable healthcare services for diabetics. Moreover, this paper has tried to improve the reliability design of the service-oriented architecture (SOA) of traditional insulin pump therapy by system thinking.

Моделирование процесса определения технического состояния тяговых электродвигателей электровозов 2ЭС6

Or positive results in reducing the number of failures of electric traction engines, predictive diagnostics in operation is proposed. The development of malfunctions in electric traction engines directly affects the registration of analog signal values by on-board equipment. Some distinctive criteria have been identified by which the technical condition of electric traction engines can be assessed. The previously developed algorithm for searching for electrical damage has been improved. The presence of a difference in armature current between adjacent bogies and pairs of the same type of electric traction engines is pointed out, the dependence between a serviceable and faulty electric traction engine in the form of discrepancy in correlation coefficients is revealed. All the revealed conditions are added to the algorithm for determining the technical condition, the processes of which are built on the KNIME intelligent analysis platform. The process of determining the technical condition with the output of the result on the serviceability / malfunction of the electric traction engine is modeled. A pair of electric traction motors with a potential malfunction is also identified. The relative modeling error, which is at an average level, allows us to partially solve the problem of occurrence of failures of electric traction engines during operation. The application of the model along with the existing methods improves the quality of predictive diagnostics of modern locomotive equipment.

Relevance of Electrical Services Engineers in Construction and Building Services

It is now a common phenomenon in building services that some builders/clients call for the services of the electrical contractor/technicians to carry out an electrical installation without the provision or availability of standard electrical services drawings, at times due to the negligence of the builder/client about the importance of electrical services drawings or in other to reduce cost, which is detrimental and hazardous to the building, pieces of equipment installed or the occupants in the future. This paper analyses the relevance of electrical services engineers in construction and building services. A well-structured online survey was adopted and shared with different engineering platforms where building and construction professionals are to know the practice at various building and construction sites, and a total of 230 responses were collected, the data collected were examined using the descriptive statistics method with good pictorial representation. The result of the survey shows that 20% of the respondents complained about the absence of electrical services drawings, 38% complained that the electrical services drawings provided are not practicable, and 42% of the respondents talked about the availability of relevant electrical services drawings. The analysis from this study confirms that several electrical installations were carried out without the provision of practicable electrical services drawings, especially in domestic installations. It is recommended that the services of qualified electrical services engineers should be employed for standard electrical services drawings, which will give detailed information about the method of wiring, the suitable size/type of distribution, and the protection scheme for lighting and power installations in conformity with the appropriate standard and regulations for effective and well-balanced electrical services.

Towards Metaverse with Diversified Applications: Service Native Architecture

With the advancement of science and technology, Metaverse will empower the entity economy and social development, and stimulate the development potential of industries such as smart city. The current chimney-style application creation process is cumbersome, which cannot support the application diversification and efficient, flexible and open service provision methods, so it cannot meet the needs of the rapid development of the Metaverse. By introducing a service engine layer that encapsulates basic service capabilities, this research proposes a Metaverse application architecture based on service native, which has characteristics of function scalability, orchestration automation, system openness, full-type access, etc. The basic service capabilities based on this architecture can support diverse needs of Metaverse applications.

Operationalization of life cycle engineering

Life cycle engineering (LCE) was introduced in the early 1990s with a main focus on designing products to reduce their environmental impact in a life cycle perspective. In the meantime, the world has seen a dramatic increase in environmental pollution despite the significant eco-efficiency improvement of individual products and services, highlighting the gap between bottom-up LCE activities and top-down sustainability concepts such as planetary boundaries that reflect the limited carrying capacity of the climate- and ecosystems of the world. This accelerates the need to address environmental sustainability as an absolute in the engineering of products and services, and this paper introduces a structured approach to bridge the gap between the top-down and bottom-up perspectives. Building on a disaggregated IPAT identity, the approach supports identifying potential mitigation options as input for LCE activities. A case study on cement products is used to demonstrate the application of the approach.