Service Engineering Research Articles

Condition-based maintenance for multi-component systems: A scalable optimization model with two thresholds

Many original equipment manufacturers (OEMs) provide customized after-sales service contracts tailored to their customers’ specific requirements. While these customized offerings may increase customer satisfaction and loyalty, they are likely more expensive, and that in times that OEMs are striving to reduce maintenance costs and ease the workload of their service engineers. To address this challenge, we introduce a quantitative methodology for shaping maintenance policies that minimize overall maintenance costs for systems comprising multiple heterogeneous components over a finite lifespan. Our proposed two-threshold condition-based maintenance policy incorporates scheduled visits and semi-urgent interventions, using component-level control thresholds to preventively trigger component replacements. Scheduled visits provide opportunities for grouping component replacements, capitalizing on positive economic dependencies.Our optimization model and solution methodology are tailored to systems consisting of numerous components. We assume a fixed time interval between consecutive scheduled visits, allowing us to employ a decomposition approach that ensures model scalability. The optimal policy for each component is determined by formulating a single-unit replacement model as a finite horizon Markov Decision Problem solved via dynamic programming. Simultaneously, at system level, we optimize the maintenance interval for the entire system using an iterative approach.The results of our case study highlight that complementing scheduled visits with semi-urgent interventions - both triggering preventive replacements - leads to a reduction in the volume of corrective maintenance. From a practical standpoint, our findings offer valuable insights for OEMs seeking to enhance their after-sales service contracts while concurrently reducing maintenance-related costs. Specifically, our model is particularly valuable for OEMs that service systems with high shutdown costs, rely heavily on customer satisfaction, and favor more attractive policies for their service engineers (i.e., reducing the number of emergency corrective interventions).

Anomaly Sign Detection for Automatic Ticket Gates by the Histogram Limitation Method

It is crucial to appropriately maintain automatic ticket gates (ATGs) to keep transportation operating smoothly in urban areas. Although the average failure rate of new ATGs is extremely low, continuous operation for many years might lead to unstable performance due to deterioration, and the need for periodic maintenance to avoid fatal faults might halt operations for extended periods. To detect anomalies at an early stage, “anomaly signs” can be utilized to flag ATGs for maintenance by service engineers before anomalies occur. In addition, to minimize the cost of ATG monitoring, the necessary computing resources should be minimized, which means using only light-weight statistical methods rather than deep learning or machine learning. In this paper, we focus on the automatic separation modules inside ATGs that separate multiple tickets by complicated mechatronic controls because this module is the major cause of maintenance calls from station attendants. We propose a simple anomaly sign detection, called the histogram limitation method (HLM). We evaluated the anomaly sign scores over time with maintenance timing and compared them with the conventional fast unsupervised anomaly detection method, Histogram-Based Outlier Score (HBOS) widely used in various domains. The experimental results using real field ATG monitoring data show that HLM successfully detected anomaly signs before a maintenance call was necessary, which is better performance compared with HBOS. Despite being a simple modification based on HBOS, HLM also provides anomaly sign scores that agree adequately with assessments by maintenance service engineers.

Circular Economy in Heat Supply Systems for Buildings: An Overview of the End of Life of System Components and Existing Evaluation Systems and Products

Abstract In order to achieve climate protection targets, many heating systems must be converted to renewable energies and more efficient systems. Most of residential buildings in Germany are heated with natural gas (50 %), 25 % with an oil. Around 45 % of the heating systems are older than 15 years, 20,5 % are even older than 25 years. Therefore, a high replacement rate is to be expected in the next few years. In the context of circular economy, the accumulating materials should remain in the material cycle. Some materials, such as metals, can be recycled easily. However, building services engineering, in particular heat supply, has become increasingly complex. This paper focuses on the state of the circular economy of heat supply systems for buildings. Firstly, a detailed examination of products utilized in heat supply systems is undertaken. Secondly, an assessment of the end-of-life scenarios for these components was conducted, considering disposal routes and recycling rates. Lastly, an evaluation of assessment systems fostering a circular economy regarding heat supply systems is performed. The aim of the work is to provide an overview of the state of the art with regard to circular economy in heat supply and thereby draw conclusions as to where potentials and obstacles exist.

Predicting effects of tunnel throttling of annular freeway vehicular flow by a continuum model

Fluid flow throttling is common in industrial and building services engineering. Similar tunnel throttling of vehicular flow is caused by the abrupt number reduction of roadway lane, as the tunnel has a lower lane number than in the roadway normal segment. To predict the effects of tunnel throttling of annular freeway vehicular flow, a three-lane continuum model is developed. Lane III of the tunnel is completely blocked due to the need of tunnel rehabilitation, etc. There exists mandatory net lane-changing rate from lane III to lane II just upstream of the tunnel entrance, which is described by a model of random number generated through a golden section analysis. The net-changing rate between adjacent lanes is modeled using a lane-changing time expressed explicitly in algebraic form. This paper assumes that the annular freeway has a total length of 100 km, a two-lane tunnel of length 2 km with a speed limit of 80 km/h. The free flow speeds on lanes I, II and III are assumed to be 110, 100 and 90 km/h respectively. Based on the three-lane continuum model, numerical simulations of vehicular flows on the annular freeway with such a tunnel are conducted with a reliable numerical method of 3rd-order accuracy. Numerical results reveal that the vehicular flow has a smaller threshold of traffic jam formation in comparison with the case without tunnel throttling. Vehicle fuel consumption can be estimated by interpolation with time averaged grid traffic speed and an assumed curve of vehicle performance. The vehicle fuel consumption is lane number dependent, distributes with initial density concavely, ranging from 5.56 to 8.00 L. Tunnel throttling leads to an earlier traffic jam formation in comparison with the case without tunnel throttling.

Improving Health and Safety Performance of Construction through Lean Construction in Ghana : Drivers, Enablers and Constraints

The aim of this paper was to see how lean technology may be applied to improve safety and health performance in Ghana's building construction sector. A structured questionnaire was used to gather data from civil/structural engineers, architects, construction managers, services engineers, and quantity surveyors that work in the construction industry. The sample was chosen using the purposeful sampling technique, taking into account the construction experts' years of experience. The findings reveal that, building construction projects in Ghana may perform better if lean construction methods are applied correctly. Based on this finding, it is recommended that training, planning and proper layout of construction site so as to eliminate overlapping of movements on site, and building trust in working relations and working together as an effective team where the key strategies for improving health and safety performance of projects through lean construction technology.

Optimization of the parameters for diagnosing engine crankcase gases

The paper considers the problem of diagnosing automotive diesel consumption in the parameters of crankcase gases. The effect of velocity, temperature, load mode of the engine to changes in the values of diagnostic parameters. The article will be interesting technical service engineers, machine operators, students and graduate students studying in the relevant fi elds.

A survey of gamma camera and SPECT/CT quality control programs across a sample of public hospitals in Australia.

Performance testing of gamma cameras and single photon computed tomography/computed tomography (SPECT/CT) systems is not subject to regulatory requirements across states and territories in Australia. Internationally recognised testing standards from organisations such as the National Electrical Manufacturers Association (NEMA) describe methodologies for recommended tests. However, variations exist in suggested quality control (QC) schedules from professional bodies such as the Australia and New Zealand Society of Nuclear Medicine (ANZSNM). In this study, a survey was conducted to benchmark current QC programs across a selected sample of eight standalone and networked Australian public hospitals. Vendor-specific flood-field uniformity (intrinsic or extrinsic/system) verification without photomultiplier (PMT) tuning and CT QC were performed at all sites. Weekly and monthly PMT tuning followed by intrinsic flood-field verifications were performed at most sites. At least half of the sites performed monthly centre of rotation (COR) offset verifications. SPECT/CT alignment calibrations and verifications were undertaken by service engineers at all sites, and periodic verifications were performed by local staff at varying frequencies. Variations were observed for other periodic QC tests such as spatial resolution and planar sensitivity. Similarly, variations were observed for tests specific to whole-body systems and SPECT systems. Most sites checked daily and periodic QC results against pass/fail criteria set by vendors. Additional analyses of the QC results, including trend analysis and periodic reviews, were not common practice. The lack of regulatory requirements is likely to have led to variations in QC tests that are generally either harder to perform or are more labour intensive.

IOT based noise pollution and water quality monitoring system

Presently, noise pollution has become a very big issue around the world. The adverse effects of this pollution include hearing impairment, negative social behaviour, annoyance, sleep disturbance and intelligibility to understand people’s speech. In learning context, noise can affect understanding and behaviour of people and places with high noise level are not suitable for learning and teaching process. Internet of Things (IoT) technology is one of the best choices to monitor the noise or sound intensity in the environment for the safety of human being. The aim of this paper is to deliver a development of an IoT based noise monitoring system comprises of a sound sensor, an IoT platform called Node MCU, LCD and LEDs. The system will provide a real-time alert if the noise exceeds the threshold noise limit set by Environmental Department of Health standard. Equipped with an Android application, the data from the sound sensor will be transferred into the cloud server and subsequently transferred into the app for display and to enable remote monitoring. A case study is carried out using the developed prototype to ascertain the noise comfort for University Technology Malaysia (UTM) students for studying or learning purpose. The sound level is measured for two different days during weekend and weekday. Based on Charted Institution of Building Service Engineers (CIBSE), 60dBA is the permissible ambient level and any readings that above 60dBA can interrupt speech intelligibility.

Spare parts recommendation for corrective maintenance of capital goods considering demand dependency

We consider a maintenance service provider that services geographically dispersed customers with its local service engineers. Traditionally, when a system failure is reported, a service engineer makes a diagnostic visit to the customer’s location to perform corrective maintenance. If spare parts are required, they are ordered and a second visit is scheduled at a later date to complete the corrective maintenance. In this paper, the service provider can proactively send spare parts to the customer to avoid the costly second visit. Motivated by a real-world problem in the high-tech industry, our model considers the cost of a second visit, fixed shipment costs, retrieval costs for the parts that are sent to the customer, and send-back costs for the parts that are sent but not used for corrective maintenance. The uncertainty in the set of parts required for corrective maintenance is modeled with a general distribution that can capture the dependencies between demands for different spare parts. We formulate an integer linear program to find the optimal set of spare parts that minimizes the expected total cost. We derive analytical results for the structure of the optimal policy and compare the optimal policy with two benchmark policies from practice. We observe that the policies from practice often find the optimal policy, and a new heuristic policy that exploits the structure of the optimal policy, on average, performs better than the benchmark policies.

A Comprehensive Comparison of IBM Cloud and Microsoft Azure

The ever-growing demand for scalability, agility, and cost-effectiveness has fuelled cloud computing to the forefront of modern IT infrastructure. According to Precedence Research, the global cloud computing market size was valued at USD 480 billion in 2022 and is expected to hit USD 2297.37 billion by 2032 with a registered CAGR of 17% from 2023 to 2032 [1]. The growth of cloud computing is driven by various factors such as the rapid evolution of technology and the globalization of businesses. Cloud computing is already embraced in various industries like Financial Services, Manufacturing, Healthcare, Retail, Education, and Architecture Engineering & Construction (AEC), where it streamlines operations, enhances collaboration, and revolutionizes processes. Cloud computing holds immense potential, especially in sectors like healthcare, real estate, tourism, and small and medium enterprises, where it will facilitate faster and more informed decision-making processes through data collection and analysis. Additionally, cloud technology is revolutionizing government sectors by driving cost savings, enhancing efficiency, and promoting transparency and citizen engagement. With the increasing number of cloud computing service providers such as IBM, Microsoft, Google, Amazon, and others, it becomes crucial to delve into their technical nuances. Understanding how each provider's offerings align with specific business requirements, technical specifications, and future scalability is paramount for organizations venturing into their cloud journey. The main purpose of this paper is to explore and evaluate the technical dimensions of IBM Cloud and Microsoft Azure and understand its future potential.

Improving Natural and Artificial Lighting in Coastal Architecture Classrooms: Insights and Applications

This research examines the natural and artificial lighting performance comparison in an architecture classroom at a university in southern Thailand and gives principles for enhancing lighting design. The sample for the study was classroom spaces. The efficacy of natural and artificial lighting was studied using static and dynamic models, and data were obtained using a 4 in 1 multi-function environmental meter at various times of the day. The current study adopted the IESNA (Illuminating Engineering Society of North America) and CIBSE (Chartered Institution of Building Services Engineers) lighting standards for the performance comparison analysis. The results showed that the natural light in the classrooms did not satisfy the standards for lighting levels. In contrast, the artificial lighting was more effective but raised some issues with uniformity and glare. The study offers recommendations for improving lighting effectiveness, maximizing natural light, reducing energy consumption, improving the uniformity of artificial illumination, addressing issues with various classroom lighting designs, and creating more comfortable and realistic learning environments.

Optimizing bandwidth utilization and traffic control in ISP networks for enhanced smart agriculture.

As the demand for high-bandwidth Internet connections continues to surge, industries are exploring innovative ways to harness this connectivity, and smart agriculture stands at the forefront of this evolution. In this paper, we delve into the challenges faced by Internet Service Providers (ISPs) in efficiently managing bandwidth and traffic within their networks. We propose a synergy between two pivotal technologies, Multi-Protocol Label Switching-Traffic Engineering (MPLS-TE) and Diffserv Quality of Service (Diffserv-QoS), which have implications beyond traditional networks and resonate strongly with the realm of smart agriculture. The increasing adoption of technology in agriculture relies heavily on real-time data, remote monitoring, and automated processes. This dynamic nature requires robust and reliable high-bandwidth connections to facilitate data flow between sensors, devices, and central management systems. By optimizing bandwidth utilization through MPLS-TE and implementing traffic control mechanisms with Diffserv-QoS, ISPs can create a resilient network foundation for smart agriculture applications. The integration of MPLS-TE and Diffserv-QoS has resulted in significant enhancements in throughput and a considerable reduction in Jitter. Employment of the IPv4 header has demonstrated impressive outcomes, achieving a throughput of 5.83 Mbps and reducing Jitter to 3 msec.

Traffic engineering and quality of service in hybrid software defined networks

Traffic engineering and quality of service in hybrid software defined networks

Industrial application of a low-cost structural health monitoring system in large-scale airframe tests

A small, novel, integrated SHM system has been deployed during full-scale testing of a wing fatigue test for several weeks and a fuselage pressurisation test for several months. Complementary NDE measurement techniques were combined, with inputs from visible and infrared optical sensors, as well as resistance strain gauges. Sensor units were deployed at regions of interest and integrated board computers permitted near real-time data processing. The outputs were full-field measurement datasets from digital image correlation and thermoelastic stress analysis systems. Changes in these datasets in the regions of interest were successfully quantified using orthogonal decomposition and were indicative of changes in the condition of the structure. The results from these case studies demonstrate that this system can be successfully deployed in spatially restricted areas within airframe structures to monitor crack growth. The low cost and small footprint of the system presents the opportunity for installation of arrays of similar sensors for both test and in-service data collection. Near real-time data processing would allow timely reporting to service engineers, informing maintenance or operational decisions.

A Study on Automated Problem Troubleshooting in Cloud Environments with Rule Induction and Verification

In a vast majority of cases, remediation of IT issues encoded into domain-specific or user-defined alerts occurring in cloud environments and customer ecosystems suffers from accurate recommendations, which could be supplied in a timely manner for recovery of performance degradations. This is hard to realize by furnishing those abnormality definitions with appropriate expert knowledge, which varies from one environment to another. At the same time, in many support cases, the reported problems under Global Support Services (GSS) or Site Reliability Engineering (SRE) treatment ultimately go down to the product teams, making them waste costly development hours on investigating self-monitoring metrics of our solutions. Therefore, the lack of a systematic approach to adopting AI Ops significantly impacts the mean-time-to-resolution (MTTR) rates of problems/alerts. This would imply building, maintaining, and continuously improving/annotating a data store of insights on which ML models are trained and generalized across the whole customer base and corporate cloud services. Our ongoing study aligns with this vision and validates an approach that learns the alert resolution patterns in such a global setting and explains them using interpretable AI methodologies. The knowledge store of causative rules is then applied to predicting potential sources of the application degradation reflected in an active alert instance. In this communication, we share our experiences with a prototype solution and up-to-date analysis demonstrating how root conditions are discovered accurately for a specific type of problem. It is validated against the historical data of resolutions performed by heavy manual development efforts. We also offer experts a Dempster–Shafer theory-based rule verification framework as a what-if analysis tool to test their hypotheses about the underlying environment.

Project-based learning through the lens of SEEM: enhancing implementation in the Brazilian context

PurposeThis study aims to mitigate the inherent challenges associated with implementing project-based learning (PjBL) by integrating it with the service engineering methodology (SEEM). The study demonstrates that combining PjBL with a methodological approach provides a step-by-step procedure that facilitates the practical application of PjBL and preserves the development of competencies inherent to PjBL.Design/methodology/approachAction research methodology was used to assess the effectiveness of combining PjBL learning strategy with SEEM. Data was collected through observations, questionnaires and focus group discussions to evaluate students’ expectations and perceptions of this combination.FindingsThe results show that PjBL implementation combined with SEEM enabled the organization of class dynamics, helping to mitigate difficulties encountered in the application of PjBL. Students conveyed that the integration of PjBL with SEEM afforded them a guiding structure without compromising their autonomy in decision-making for proposed solutions. It proved efficacious in honing skills pertinent to service design and analysis, teamwork, solution formulation, creativity and innovation stimulation.Research limitations/implicationsThis research has been limited to four classes in one university in Brazil. Besides, PjBL was combined with only one methodology (SEEM). Therefore, this needs to be tested in broader settings and contexts.Practical implicationsThe article highlights the potential benefits of PjBL in bridging the gap between academia and the professional world while acknowledging the challenges involved in its implementation, combining PjBL with a methodology that provides a sequence of steps to be followed.Social implicationsThe social implications of implementing PjBL in higher education in the Brazilian and international contexts are multifaceted. The adoption of PjBL encourages instructors to adapt their learning strategies and align them with the evolving needs of worldwide society. Through PjBL, Brazilian and international higher education institutions may contribute to the development of individuals who are not only knowledgeable but also capable of applying their knowledge effectively in practical situations around the world.Originality/valueThe theoretical contribution lies in suggesting that combining PjBL with a methodology that provides a sequence of steps to be followed (such as that exemplified through SEEM) can address intrinsic issues that consider the complexity of PjBL implementation, preserving the development of competencies inherent to PjBL.

Adopting the service system view toward successful implementation of assistive technologies.

This study aims to provide an overview of the service system view (SSV), and the current status of its adoption for the development and implementation of assistive technology (AT). The role of ATs in the global aging scenario is anticipated; however, their diffusion is cumbersome. The SSV captures stakeholders, technologies, and their interactions as integrated systems. Based on this perspective, several approaches for designing long-term care services have been proposed that would be helpful for the successful implementation of ATs. However, the existing geriatrics and gerontology literature seldom addresses these topics. Based on a literature review, this study first illustrates the challenges of using ATs in the real world. The existing literature highlights the sociotechnical challenges of utilizing ATs, such as the changes required in care work and resistance to them. To overcome the challenges, three approaches associated with the SSV have been introduced: service design, service engineering and living labs. This paper also introduces recent national projects in Japan that have adopted these approaches. As the importance of the SSV is growing for the successful implementation of ATs, the ability to adopt the SSV and its approaches is anticipated. In relation to geriatrics and gerontology studies, the impact on older adults' quality of life, as well as the economic effect, needs to be analyzed in future research. Geriatr Gerontol Int 2024; 24: 74-80.

Virtualization and Online Engineering of the Administrative Services in Universities

Virtualization and online engineering of services are emerging as key themes that will profoundly influence society and industry in the near and distant future. This paper focuses on the transformation of administrative services in universities into virtual services through online engineering. This transition presents challenges not only to universities in Bulgaria but also worldwide. Given the significant impact of technology on the daily operations of universities, it is evident that the digital divide is an issue worthy of investigation. Disparities in the adoption of online administrative services can and will lead to inconsistencies in the economic development of universities. This article aims to explore some of the challenges associated with virtualization and online engineering of administrative services in universities and offers insights into how to address them.

Flexible Couplings Design Management System for Generating Plants

This study has provided a computer programming method of solving the problem of quick design and selection of tyre flexible couplings applied in power generating plants. First, a theoretical design model was developed for tyre flexible couplings by relating transmission power of the couplings to the power ratings and the service factor of generating plant. On this basis, standard coupling sizes, and dimensions were selected at varying speeds, 1000, 2000 and 3000 rpm, from which the best choice of waste tyre coupling was made. Computer software package was developed using python language for robust and quick selection of the best coupling sign for a given power ratings of the generating plant. A case study results showed that for over 16 hours of running the generating plant, the selected service factor (1.5), engine speed (1000 rpm), coupling size (F 60), bore diameters (42-48 mm) and power rating (11.10 kW) performed satisfactorily. Couplings selection results of the five cases obtained from the computer package were consistent with the ones obtained manually. Computer package performed better with time saving of more than 99%. Therefore the system is capable of selecting the best tyre flexible couplings for a given generating plant power operated within the stated (16) hours without recourse to manual design and flexible coupling standards.

HIERARCHICAL MODEL FOR BUILDING COMPOSITE WEB SERVICES

The current evolution of disseminated computer program frameworks is characterized by a growing adherence to the principles of service-oriented engineering (SOA). Simultaneously, these frameworks are becoming more intricate, with an increasing number of components and more complex data connections between them. This situation underscores the importance of employing mechanisms to unify artifacts in the process of developing composite web services, which govern, among other aspects, the architectural plane of the frameworks under construction. A model for constructing composite web services is suggested as a suitable tool, implemented in accordance with a hierarchical approach, intended for use in designing distributed systems. Model is constructed over an assumption that coordination of the components of a composite web service is carried out in a centralized manner. in accordance with the orchestration model. To implement formalization and obtain, based on analytical representations, the corresponding software implementations, it has been decided to use the DEVS mathematical apparatus. The aspect of software implementation is considered pivotal in determining the feasibility of automating the acquisition of composite web services that operate within the orchestration model. Obtained research results has been interpreted as a conrmation of the eectiveness of this approach on the basis of the scenario of querying the database. Resulting artifacts have been represented with UML notation. The relationship between analytical representations and corresponding software implementations has also been demonstrated. Usage of the DEVS Suite tools has made it possible to visualize the process of simulation - to obtain estimated values of the indexes of the resulting solutions