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9 pages, 214 KiB

Open AccessEditorial

Systems Engineering: Availability and Reliability

by Katarzyna Antosz, Jose Machado, Dariusz Mazurkiewicz, Dario Antonelli and Filomena Soares

Appl. Sci. 2022, 12(5), 2504; https://doi.org/10.3390/app12052504 - 28 Feb 2022

Cited by 18 | Viewed by 2953

Abstract

Current trends in Industry 4 [...] Full article

(This article belongs to the Special Issue Systems Engineering: Availability and Reliability)

Research

Jump to: Editorial

14 pages, 5102 KiB

Open AccessFeature PaperArticle

Influence of Contamination of Gear Oils in Relation to Time of Operation on Their Lubricity

by Leszek Gil, Krzysztof Przystupa, Daniel Pieniak, Edward Kozłowski, Katarzyna Antosz, Konrad Gauda and Paweł Izdebski

Appl. Sci. 2021, 11(24), 11835; https://doi.org/10.3390/app112411835 - 13 Dec 2021

Cited by 6 | Viewed by 3142

Abstract

The quality and reliability of consumables, including gear oils, results in the failure-free operation of the transmission components in heavy trucks. It is known that oil viscosity is essential for all lubricated tribopairs for wear and friction reduction in all vehicles with a [...] Read more.

The quality and reliability of consumables, including gear oils, results in the failure-free operation of the transmission components in heavy trucks. It is known that oil viscosity is essential for all lubricated tribopairs for wear and friction reduction in all vehicles with a gearbox. Viscosity may be influenced by the contamination that wear products can impart on the oil. Oil contamination can also affect lubrication efficiency in the boundary friction conditions in gearboxes where slips occur (including bevel and hypoid gearboxes). The present research focused on this issue. An obvious hypothesis was adopted, where it was theorized that exploiting the contaminants that are present in gear oil may affect how the lubricating properties of gear oils deteriorate. Laboratory tests were performed on contaminants that are commonly found in gear oil using the Parker Laser CM20. The study was designed to identify a number of different solid particles that are present in oil. At the second stage, friction tests were conducted for a friction couple “ball-on-disc” in an oil bath at 90 °C on a CSM microtribometer. The quantitative contamination of the gear oils that contained solid particles and the curves representing the friction coefficients of fresh oils with a history of exploitation were compared. The test results were statistically analysed. Exploitation was shown to have a significant impact on the contamination of gear oils. It was revealed that the contamination and the mileage had no effect on the tested oils. Full article

(This article belongs to the Special Issue Systems Engineering: Availability and Reliability)

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22 pages, 4561 KiB

Open AccessArticle

Dynamic Analysis Method for Fault Propagation Behaviour of Machining Centres

by Liming Mu, Yingzhi Zhang, Jintong Liu, Fenli Zhai and Jie Song

Appl. Sci. 2021, 11(14), 6525; https://doi.org/10.3390/app11146525 - 15 Jul 2021

Cited by 7 | Viewed by 2260

Abstract

Fault propagation behaviour analysis is the basis of fault diagnosis and health maintenance. Traditional fault propagation studies are mostly based on a priori knowledge of a causality model combined with rule-based reasoning, disregarding the limitations of experience and the dynamic characteristics of the [...] Read more.

Fault propagation behaviour analysis is the basis of fault diagnosis and health maintenance. Traditional fault propagation studies are mostly based on a priori knowledge of a causality model combined with rule-based reasoning, disregarding the limitations of experience and the dynamic characteristics of the system that cause deviations in the identification of critical fault sources. Thus, this paper proposes a dynamic analysis method for fault propagation behaviour of machining centres that combines fault propagation mechanisms with model structure characteristics. This paper uses the design structure matrix (DSM) to establish the fault propagation hierarchy structure model. Considering the correlation of fault time, the fault probability function of a component is obtained and the fault influence degree of nodes are calculated. By introducing the Copula and Coupling degree functions, the fault influence degree of the edges between the same level and different levels are calculated, respectively. This paper constructs a fault propagation intensity model by integrating the edge betweenness and uses it as an index to analyze real-time fault propagation behaviour. Finally, a certain type of machining centre is taken as an example for specific application. This study can provide as a reference for the fault maintenance and reliability growth of a machining centre. Full article

(This article belongs to the Special Issue Systems Engineering: Availability and Reliability)

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31 pages, 8708 KiB

Open AccessArticle

A Hybrid Multi-Objective Evolutionary Algorithm-Based Semantic Foundation for Sustainable Distributed Manufacturing Systems

by Veera Babu Ramakurthi, V. K. Manupati, José Machado and Leonilde Varela

Appl. Sci. 2021, 11(14), 6314; https://doi.org/10.3390/app11146314 - 8 Jul 2021

Cited by 13 | Viewed by 2956

Abstract

Rising energy prices, increasing maintenance costs, and strict environmental regimes have augmented the already existing pressure on the contemporary manufacturing environment. Although the decentralization of supply chain has led to rapid advancements in manufacturing systems, finding an efficient supplier simultaneously from the pool [...] Read more.

Rising energy prices, increasing maintenance costs, and strict environmental regimes have augmented the already existing pressure on the contemporary manufacturing environment. Although the decentralization of supply chain has led to rapid advancements in manufacturing systems, finding an efficient supplier simultaneously from the pool of available ones as per customer requirement and enhancing the process planning and scheduling functions are the predominant approaches still needed to be addressed. Therefore, this paper aims to address this issue by considering a set of gear manufacturing industries located across India as a case study. An integrated classifier-assisted evolutionary multi-objective evolutionary approach is proposed for solving the objectives of makespan, energy consumption, and increased service utilization rate, interoperability, and reliability. To execute the approach initially, text-mining-based supervised machine-learning models, namely Decision Tree, Naïve Bayes, Random Forest, and Support Vector Machines (SVM) were adopted for the classification of suppliers into task-specific suppliers. Following this, with the identified suppliers as input, the problem was formulated as a multi-objective Mixed-Integer Linear Programming (MILP) model. We then proposed a Hybrid Multi-Objective Moth Flame Optimization algorithm (HMFO) to optimize process planning and scheduling functions. Numerical experiments have been carried out with the formulated problem for 10 different instances, along with a comparison of the results with a Non-Dominated Sorting Genetic Algorithm (NSGA-II) to illustrate the feasibility of the approach. Full article

(This article belongs to the Special Issue Systems Engineering: Availability and Reliability)

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17 pages, 3670 KiB

Open AccessArticle

Statistical Reliability Assessment for Small Sample of Failure Data of Dumper Diesel Engines Based on Power Law Process and Maximum Likelihood Estimation

by Brajeshkumar Kishorilal Dinkar, Alok Kumar Mukhopadhyay, Somnath Chattopadhyaya, Shubham Sharma, Firoz Alam and José Machado

Appl. Sci. 2021, 11(12), 5387; https://doi.org/10.3390/app11125387 - 10 Jun 2021

Cited by 11 | Viewed by 2780

Abstract

Dumpers or dump trucks are used all over the world to move overburden from many opencast mines. Diesel engines are the main driving force behind the trucks. The frequency of damage due to the failure of diesel engines is enormous. Therefore, efforts are [...] Read more.

Dumpers or dump trucks are used all over the world to move overburden from many opencast mines. Diesel engines are the main driving force behind the trucks. The frequency of damage due to the failure of diesel engines is enormous. Therefore, efforts are necessary to analyze failure to reduce the downtime periods. A detailed analysis of engine failure at the subsystem level needs to be done. Reliability analysis and maintenance planning remain the norm in this regard. The obstacle faced while analysing the reliability of dumpers was the availability of a large number of data failures. In this paper, this issue is addressed by using Common Beta Hypothesis test and Meta-analysis test. The engine is divided into five subsystems. The result shows that all five subsystems pass the CBH test and Meta-analysis test. Accordingly, the failure data is grouped. The trend test of grouped failure data shows that the Failure data of two subsystems follows the independent and identically distributed characteristics while the remaining three do not follow it. The reliability is estimated for all five subsystems. Finally, fuel supply subsystems show the highest reliability while the lowest value is seen for self-starting subsystems. Full article

(This article belongs to the Special Issue Systems Engineering: Availability and Reliability)

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20 pages, 4744 KiB

Open AccessArticle

Proposal of a Monitoring System for Collaborative Robots to Predict Outages and to Assess Reliability Factors Exploiting Machine Learning

by Khurshid Aliev and Dario Antonelli

Appl. Sci. 2021, 11(4), 1621; https://doi.org/10.3390/app11041621 - 10 Feb 2021

Cited by 27 | Viewed by 4272

Abstract

Industry standards pertaining to Human-Robot Collaboration (HRC) impose strict safety requirements to protect human operators from danger. When a robot is equipped with dangerous tools, moves at a high speed or carries heavy loads, the current safety legislation requires the continuous on-line monitoring [...] Read more.

Industry standards pertaining to Human-Robot Collaboration (HRC) impose strict safety requirements to protect human operators from danger. When a robot is equipped with dangerous tools, moves at a high speed or carries heavy loads, the current safety legislation requires the continuous on-line monitoring of the robot’s speed and a suitable separation distance from human workers. The present paper proposes to make a virtue out of necessity by extending the scope of on-line monitoring to predicting failures and safe stops. This has been done by implementing a platform, based on open access tools and technologies, to monitor the parameters of a robot during the execution of collaborative tasks. An automatic machine learning (ML) tool on the edge of the network can help to perform the on-line predictions of possible outages of collaborative robots, especially as a consequence of human-robot interactions. By exploiting the on-line monitoring system, it is possible to increase the reliability of collaborative work, by eliminating any unplanned downtimes during execution of the tasks, by maximising trust in safe interactions and by increasing the robot’s lifetime. The proposed framework demonstrates a data management technique in industrial robots considered as a physical cyber-system. Using an assembly case study, the parameters of a robot have been collected and fed to an automatic ML model in order to identify the most significant reliability factors and to predict the necessity of safe stops of the robot. Moreover, the data acquired from the case study have been used to monitor the manipulator’ joints; to predict cobot autonomy and to provide predictive maintenance notifications and alerts to the end-users and vendors. Full article

(This article belongs to the Special Issue Systems Engineering: Availability and Reliability)

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14 pages, 1574 KiB

Open AccessFeature PaperArticle

The Method of Production Scheduling with Uncertainties Using the Ants Colony Optimisation

by Iwona Paprocka, Damian Krenczyk and Anna Burduk

Appl. Sci. 2021, 11(1), 171; https://doi.org/10.3390/app11010171 - 27 Dec 2020

Cited by 13 | Viewed by 2119

Abstract

Production and maintenance tasks apply for access to the same resources. Maintenance-related machine downtime reduces productivity, but the costs incurred due to unplanned machine failures often outweigh the costs associated with predictive maintenance. Costs incurred due to unplanned machine failure include corrective maintenance, [...] Read more.

Production and maintenance tasks apply for access to the same resources. Maintenance-related machine downtime reduces productivity, but the costs incurred due to unplanned machine failures often outweigh the costs associated with predictive maintenance. Costs incurred due to unplanned machine failure include corrective maintenance, reworks, delays in deliveries, breaks in the work of employees and machines. Therefore, scheduling of production and maintenance tasks should be considered jointly. The problem of generating a predictive schedule with given constrains is considered. The objective of the paper is to develop a scheduling method that reflects the operation of the production system and nature of disturbances. The original value of the paper is the development of the method of a basic schedule generation with the application of the Ant Colony Optimisation. A predictive schedule is built by planning the technical inspection of the machine at time of the predicted failure-free time. The numerical simulations are performed for job/flow shop systems. Full article

(This article belongs to the Special Issue Systems Engineering: Availability and Reliability)

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18 pages, 4162 KiB

Open AccessArticle

Application of Predictive Maintenance Concepts Using Artificial Intelligence Tools

by Diogo Cardoso and Luís Ferreira

Appl. Sci. 2021, 11(1), 18; https://doi.org/10.3390/app11010018 - 22 Dec 2020

Cited by 47 | Viewed by 10296

Abstract

The growing competitiveness of the market, coupled with the increase in automation driven with the advent of Industry 4.0, highlights the importance of maintenance within organizations. At the same time, the amount of data capable of being extracted from industrial systems has increased [...] Read more.

The growing competitiveness of the market, coupled with the increase in automation driven with the advent of Industry 4.0, highlights the importance of maintenance within organizations. At the same time, the amount of data capable of being extracted from industrial systems has increased exponentially due to the proliferation of sensors, transmission devices and data storage via Internet of Things. These data, when processed and analyzed, can provide valuable information and knowledge about the equipment, allowing a move towards predictive maintenance. Maintenance is fundamental to a company’s competitiveness, since actions taken at this level have a direct impact on aspects such as cost and quality of products. Hence, equipment failures need to be identified and resolved. Artificial Intelligence tools, in particular Machine Learning, exhibit enormous potential in the analysis of large amounts of data, now readily available, thus aiming to improve the availability of systems, reducing maintenance costs, and increasing operational performance and support in decision making. In this dissertation, Artificial Intelligence tools, more specifically Machine Learning, are applied to a set of data made available online and the specifics of this implementation are analyzed as well as the definition of methodologies, in order to provide information and tools to the maintenance area. Full article

(This article belongs to the Special Issue Systems Engineering: Availability and Reliability)

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16 pages, 6483 KiB

Open AccessArticle

Availability Estimation of Air Compression and Nitrogen Generation Systems in LNG-FPSO Depending on Design Stages

by Youngkyun Seo, Jung-Yeul Jung, Seongjong Han and Kwangu Kang

Appl. Sci. 2020, 10(23), 8657; https://doi.org/10.3390/app10238657 - 3 Dec 2020

Cited by 3 | Viewed by 4330

Abstract

This study estimated availability of an air compression system and a nitrogen generation system in liquefied natural gas—floating production storage and offloading unit (LNG-FPSO) with different design stages to investigate the gap between the availability at the early design stage and that at [...] Read more.

This study estimated availability of an air compression system and a nitrogen generation system in liquefied natural gas—floating production storage and offloading unit (LNG-FPSO) with different design stages to investigate the gap between the availability at the early design stage and that at the late design stage. Although availability estimation in the early design stage is more important than the late design stage, it is difficult to estimate the availability accurately in the early design stage. The design stage was divided into three depending on the design progress. Monte Carlo simulation technique was employed for the availability estimation. The results of the availability estimation showed that there was 0.434% difference between the early and late design stages. This meant that the availability in the early design stage was underestimated due to limited information. A sensitivity analysis was performed to investigate critical factors affecting the results. The investigated factors were failure rate, repair time, redundant equipment, and modified preventive maintenance schedule. The most critical factor was redundant equipment. It increased 0.486% availability. Full article

(This article belongs to the Special Issue Systems Engineering: Availability and Reliability)

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16 pages, 2794 KiB

Open AccessArticle

On the Use of Importance Measures in the Reliability of Inventory Systems, Considering the Cost

by Liwei Chen, Meng Kou and Songwei Wang

Appl. Sci. 2020, 10(21), 7942; https://doi.org/10.3390/app10217942 - 9 Nov 2020

Cited by 3 | Viewed by 2830

Abstract

In order to maximize inventory benefits or minimize costs, reliability and cost of inventory control models need to be identified and analyzed. These importance measures are one important approach to recognize and evaluate system weaknesses. However, importance measures have fewer applications in inventory [...] Read more.

In order to maximize inventory benefits or minimize costs, reliability and cost of inventory control models need to be identified and analyzed. These importance measures are one important approach to recognize and evaluate system weaknesses. However, importance measures have fewer applications in inventory systems’ reliability. Considering the cost, this paper mainly discusses the reliability change of performance parameters with the importance measures in inventory systems. The calculation methods of differential importance and Birnbaum importance are studied in the inventory control model with shortages. By comparing the importance values of various parameters in the model, the optimization analysis of the inventory model can be used to identify the key parameters, so as to effectively reduce the total inventory cost. The importance order and the identification of key parameters are helpful to increase the operational efficiency of the inventory control and provide effective methods for improving the inventory management. Lastly, a case study with a shortage and limited inventory capacity is used to demonstrate the proposed model. Full article

(This article belongs to the Special Issue Systems Engineering: Availability and Reliability)

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10 pages, 3759 KiB

Open AccessFeature PaperArticle

Analysis of the Effect of Shape Factor on Cork–Rubber Composites under Small Strain Compression

by Helena Lopes, Susana Silva and José Machado

Appl. Sci. 2020, 10(20), 7177; https://doi.org/10.3390/app10207177 - 15 Oct 2020

Cited by 10 | Viewed by 2897

Abstract

Like other types of elastomers, different geometries of the same cork–rubber material present different mechanical behaviour when subject to compression between bonded plates. To validate the application of Hooke’s Law on cork–rubber materials, under compression at small strains, a set of experimental and [...] Read more.

Like other types of elastomers, different geometries of the same cork–rubber material present different mechanical behaviour when subject to compression between bonded plates. To validate the application of Hooke’s Law on cork–rubber materials, under compression at small strains, a set of experimental and numerical analyses has been conducted. Using finite element analysis, a methodology is described to relate frictionless and frictional compression between a cork–rubber sample and loading plates. Based on that, the performance of square cross-section blocks with other dimensions can be evaluated. The results obtained by this approach showed a good agreement with experimental compression tests and with outputs from other models available in the literature relating Young and apparent compression moduli. Full article

(This article belongs to the Special Issue Systems Engineering: Availability and Reliability)

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17 pages, 1288 KiB

Open AccessArticle

Reliability-Based Preventive Maintenance Strategy of Truck Unloading Systems

by Awsan Mohammed, Ahmed Ghaithan, Mashel Al-Saleh and Khalaf Al-Ofi

Appl. Sci. 2020, 10(19), 6957; https://doi.org/10.3390/app10196957 - 5 Oct 2020

Cited by 7 | Viewed by 4574

Abstract

The unloading of petroleum products is a complex and potentially dangerous operation since the unloading system contains complex interdependency components. Any failures in one of its components lead to a cut in the petroleum supply chain. Therefore, it is important to assess and [...] Read more.

The unloading of petroleum products is a complex and potentially dangerous operation since the unloading system contains complex interdependency components. Any failures in one of its components lead to a cut in the petroleum supply chain. Therefore, it is important to assess and evaluate the reliability of the unloading system in order to improve its availability. In this context, this paper presents the operation philosophy of the truck unloading system, failure modes of the components within the system, and a bottom-up approach to analyze the reliability of the system. In addition, it provides reliability data, such as failure rates, and mean time between failures of the system components. Furthermore, the reliability of the whole system was calculated and is presented for different time periods. The critical components, which are major contributors towards the system reliability, were identified. To enhance the system reliability, a reliability-based preventive maintenance strategy for the critical components was implemented. In addition, the preventive maintenance scheduling was identified based on the reliability plots of the unloading system. The best schedule for preventive maintenance of the system was determined based on the reliability function to be every 45 days for maintaining the system reliability above 0.9. Findings reveal that the reliability of the unloading system was significantly improved. For instance, the system reliability at one year improved by 80%, and this ratio increased dramatically as the time period increased. Full article

(This article belongs to the Special Issue Systems Engineering: Availability and Reliability)

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14 pages, 7836 KiB

Open AccessArticle

Investigation of Roller-Tape Contact Pair Used in Precision Mechatronic System

by Antanas Fursenko, Artūras Kilikevičius, Kristina Kilikevičienė, Sergejus Borodinas, Albinas Kasparaitis and Jonas Matijošius

Appl. Sci. 2020, 10(11), 4041; https://doi.org/10.3390/app10114041 - 11 Jun 2020

Cited by 3 | Viewed by 2806

Abstract

Smoothness of tape movement and stability of the tape area where elements are generated are very important in precision mechatronic devices where precise elements are generated on a steel tape, controlling them in real time. During movement, deformations and vibrations form in the [...] Read more.

Smoothness of tape movement and stability of the tape area where elements are generated are very important in precision mechatronic devices where precise elements are generated on a steel tape, controlling them in real time. During movement, deformations and vibrations form in the steel tape area where elements are generated as a result of imperfections of movement equipment, contact between the roller surface and the tape, and errors arising in the movement process. This article is based on the need for a detailed theoretical and experimental research of the effects occurring during the movement of the precision steel tape used in measuring systems with precision elements generated on the tape, including an investigation of the roller-tape contact. The article also aims to develop a model of the system for measuring the displacement of the tape in a raster formation device, to investigate and assess possible effects of external and internal factors on steel tape parameters. The article presents experimental research conducted for determining dynamic variables forming during the movement of a steel tape, assessing the factors that may cause raster generation errors in dynamic mode. Full article

(This article belongs to the Special Issue Systems Engineering: Availability and Reliability)

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23 pages, 2493 KiB

Open AccessArticle

A Novel Risk Assessment and Analysis Method for Correlation in a Complex System Based on Multi-Dimensional Theory

by Zeyong Jiang, Tingdi Zhao, Shihai Wang and Fuchun Ren

Appl. Sci. 2020, 10(9), 3007; https://doi.org/10.3390/app10093007 - 25 Apr 2020

Cited by 13 | Viewed by 3176

Abstract

With the rapid development of high integrations in large complex systems, such as aircraft, satellite, and railway systems, due to the increasingly complex coupling relationship between components within the system, local disturbances or faults may cause global effects on the system by fault [...] Read more.

With the rapid development of high integrations in large complex systems, such as aircraft, satellite, and railway systems, due to the increasingly complex coupling relationship between components within the system, local disturbances or faults may cause global effects on the system by fault propagation. Therefore, there are new challenges in safety analysis and risk assessment for complex systems. Aiming at analyzing and evaluating the inherent risks of the complex system with coupling correlation characteristics objectively, this paper proposes a novel risk assessment and analysis method for correlation in complex system based on multi-dimensional theory. Firstly, the formal description and coupling degree analysis method of the hierarchical structure of complex systems is established. Moreover, considering the three safety risk factors of fault propagation probability, potential severity, and fault propagation time, a multi-dimensional safety risk theory is proposed, in order to evaluate the risk of each element within the system effecting on the overall system. Furthermore, critical safety elements are identified based on Pareto rules, As Low As Reasonably Practicable (ALARP) principles, and safety risk entropy to support the preventive measures. Finally, an application of an avionics system is provided to demonstrate the effectiveness of the proposed method. Full article

(This article belongs to the Special Issue Systems Engineering: Availability and Reliability)

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21 pages, 6650 KiB

Open AccessArticle

Approach to Risk Performance Reasoning with Hidden Markov Model for Bauxite Shipping Process Safety by Handy Carriers

by Jianjun Wu, Yongxing Jin, Shenping Hu, Jiangang Fei and Yuanqiang Zhang

Appl. Sci. 2020, 10(4), 1269; https://doi.org/10.3390/app10041269 - 13 Feb 2020

Cited by 5 | Viewed by 2387

Abstract

An approach based on the hidden Markov model (HMM) is proposed for risk performance reasoning (RPR) for the bauxite shipping process by Handy carriers. The unobservable (hidden) state process in the approach aims to model the underlying risk performance, while the observation process [...] Read more.

An approach based on the hidden Markov model (HMM) is proposed for risk performance reasoning (RPR) for the bauxite shipping process by Handy carriers. The unobservable (hidden) state process in the approach aims to model the underlying risk performance, while the observation process was formed from the time series of risk factors. Within the framework, the log-likelihood probability was used as the measure of similarity between historical and current data of risk reasoning factors. Based on scalar quantization regulation and risk performance quantization regulation, the RPR approach with different step sizes was conducted on the operational case, the performance of which was evaluated in terms of effectiveness and accuracy. The reasoning performance of the HMM was tested during the validation period using three simulated scenarios and one accident scenario. The results showed significant improvement in the reasoning capacity, and satisfactory performance for numerical risk reasoning and categorical performance reasoning. The proposed model is able to provide a reference for risk performance monitoring and threat pre-warning during the bauxite shipping process. Full article

(This article belongs to the Special Issue Systems Engineering: Availability and Reliability)

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22 pages, 8561 KiB

Open AccessArticle

Risk Management for the Reliability of Robotic Assisted Treatment of Non-resectable Liver Tumors

by Doina Pisla, Vaida Calin, Iosif Birlescu, Nadim Al Hajjar, Bogdan Gherman, Corina Radu and Nicolae Plitea

Appl. Sci. 2020, 10(1), 52; https://doi.org/10.3390/app10010052 - 19 Dec 2019

Cited by 20 | Viewed by 3059

Abstract

Hepatic cancers represent an important worldwide health issue where surgery alone in most cases is not a feasible therapeutic solution since most tumors are non-resectable. Despite targeted therapies showing positive results in other areas of cancer treatment, in the case of liver tumors, [...] Read more.

Hepatic cancers represent an important worldwide health issue where surgery alone in most cases is not a feasible therapeutic solution since most tumors are non-resectable. Despite targeted therapies showing positive results in other areas of cancer treatment, in the case of liver tumors, no low-risk delivery methods have been identified. Based on a risk assessment approach, this paper proposes a technical solution in the form of a robotic system capable of achieving a reliable delivery method for targeted treatment, focusing on the patient safety and therapeutic efficiency. The design of the robotic system starts from the definition of the design constraints with respect to the medical protocol. An analytical hierarchy process is used to prioritize the data correlated with the technical characteristics of a new robotic system, aiming to minimize risks associated with the medical procedure. In a four-phase quality function deployment, the technical solution is evaluated with respect to the quality characteristics, functions, subsystems, and components aiming to achieve a safe and reliable system with high therapeutic efficiency. The results lead to the concept of HeRo, a parallel robotic system for the reliable targeted treatment of non-resectable liver tumors. Full article

(This article belongs to the Special Issue Systems Engineering: Availability and Reliability)

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17 pages, 8028 KiB

Open AccessArticle

Achievement of Accurate Robotic Arm-based Bike Frame Quality Check Using 3D Geometry Mathematical Model

by Hsiung-Cheng Lin, Bo-Ren Yu, Jen-Yu Wang, Jun-Ze Lai and Jia-Yang Wu

Appl. Sci. 2019, 9(24), 5355; https://doi.org/10.3390/app9245355 - 8 Dec 2019

Cited by 5 | Viewed by 2582

Abstract

Currently, the bike frame quality check (QC) mostly relies on human operation in industry. However, some drawbacks such as it being time-consuming, having low accuracy and involving non-computerized processes are still unavoidable. Apart from these problems,measured data are difficult to systematically analyze for [...] Read more.

Currently, the bike frame quality check (QC) mostly relies on human operation in industry. However, some drawbacks such as it being time-consuming, having low accuracy and involving non-computerized processes are still unavoidable. Apart from these problems,measured data are difficult to systematically analyze for tracking sources of product defects in the production process. For this reason, this paper aims to develop a 3D geometry mathematical model suitable for bicycle frames QC using robotic arm-based measurement. Unlike the traditional way to find coefficients of a space sphere, the proposed model requires only three check point coordinates to achieve the sphere axis coordinate and its radius. In the practical work, the contact sensor combined with the robotic arm is used to realize the compliance items measurement in shaft length, internal diameter, verticality, parallelism, etc. The proposed model is validated based on both mathematic verification and actual bike frame check. Full article

(This article belongs to the Special Issue Systems Engineering: Availability and Reliability)

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