Simultaneous Supervision Research Articles

Multi-Task Simultaneous Supervision

This paper focuses on developing a Multi-Task Simultaneous Supervision Dual Resource-Constrained Scheduling (MTSSDRC) system that considers differences in skill between operators, aiming to minimize makespan and balance operator workload. Workload balance is calculated using the Workload Smoothness Index (WSI). The mathematical model developed uses three techniques: Mixed-Integer Linear Programming (MILP), Mixed-Integer Quadratic Programming (MIQP), and Mixed-Integer Quadratically Constrained Programming (MIQCP). These techniques can handle scheduling cases on a small to medium scale. Results from MILP focus on minimizing makespan, with an additional constraint for calculating the WSI. MIQP focuses on workload balance so that the WSI value becomes an objective function. It also adds a constraint for the allowable makespan value. The result from MIQP shows that the WSI value is lower than in MILP, and the makespan values are equal to the MILP makespan value. Next, MIQCP aims to minimize makespan with a constraint for the allowable WSI value. The MIQCP model produces a makespan value adjusted to a WSI value close to zero. Finally, further analysis is presented regarding the influence of differences in operator skills based on the results of the three models. Based on these models, operators with better skills will be assigned more frequently than others.

A Dual Resource Constrained Unrelated Parallel Machine Scheduling Model Considering Tardiness and Workload Balance

The proposed study pertains to Multi-Task Simultaneous Supervision Dual Resource Constrained (MTSSDRC), which considers minimizing tardiness and workload balance. The workload balance is calculated using the Workload Smoothness Index (WSI). Additionally, the research concentrates on unrelated parallel machine schedules as they reflect the actual industry conditions in practice. This issue employs three methodologies: Mixed-Integer Linear Programming (MILP), Mixed-Integer Quadratic Problem (MIQP), and Mixed-Integer Quadratically Constrained Programming (MIQCP). The results in the MILP model focus on the value of total tardiness so that the results obtained have a smaller total tardiness value. However, it is still uncertain that the WSI value is better because no boundaries have been set between the two objective functions to achieve optimal values in the MILP model. The MIQP model focuses on the Workload Smoothness Index (WSI) value to give a limit to the total tardiness objective function. Limit values ​​are obtained from MILP model values, and the resulting WSI value becomes smaller. Moreover, the MIQCP model focuses on the total tardiness value and has limits in the form of permitted WSI. This model produces a small WSI value in accordance with the specified WSI limits while adjusting the specified total tardiness.

Unrelated Parallel Machine Considering Multi-task Simultaneous Supervision Dual Resources Constraints to Minimize Makespan

To maximize their production, many companies invest their funds into a semi-automatic machine to help them reach their fullest potential. However, many forgot to also take into account the adjustments that have to be done to the preexisting schedule because of the idle time that operators have now that the new machine has arrived. Multi-task simultaneous supervision dual resource constraints (MTSSDRC) have been the go-to method to solve that problem. Nonetheless, there is still an absence in an MTSSDRC field that involves an Unrelated Parallel Machine Scheduling Problem (UPMSP). This research proposed a model of MTSSDRC that is in line with UPMSP where the machine is a complex system and variations of machining speed can happen from a certain machine to certain jobs. This research also brought MTSSDRC closer to its real-life counterpart as a shop floor that exists in many manufacturing industries.

NSGA families for solving a dual resource-constrained problem to optimize the total tardiness and labor productivity in the spirit of sustainability

This proposed study deals with a typical dual-objective multi-task simultaneous supervision dual resource constrained (MTSSDRC) problem to optimize total tardiness and labor productivity. The problem is modeled mathematically into mixed-integer non-linear programming (MINLP) because the productivity metric is non-linear. The model is converted into a mixed-integer quadratic problem (MIQP), so it can be solved using the hierarchical approach inside a solver. The development of the new problem model and study of the solver’s performance is the first contribution to this proposal. Unfortunately, the solver is not practicable if the number of jobs is large, for example, 50 jobs only. Therefore, we proposed four metaheuristic techniques distinguished by their techniques and decoding schemes as the other contribution. We implement and modify two famous NSGA techniques, namely NSGA-II and NSGA-III, that each is equipped with two decoding scheme types which are D1 and D2. Both decoding schemes are different in the resource allocation sequence and the selection criterion. We compare the performance among metaheuristics by running them in 8 cases of small problems and 28 cases of large problems. The essential results indicate that both D1 and D2 are recommended to be implemented since D1 is more sensitive to the total tardiness objective, but D2 is better at getting solutions with better productivity metrics. Although there is no significant difference between NSGA-II and NSGA-III, we suggest using NSGA-III for practicians because it can spread solutions more balanced, indicating more varied alternatives.

Secured Framework for Smart Farming in Hydroponics with Intelligent and Precise Management based on IoT with Blockchain Technology

Hydroponics is a type of soil-free farming that uses less water and other resources than conventional soil-based farming methods. However, due to the simultaneous supervision of multiple factors, nutrition advice, and plant diagnosis system, monitoring hydroponics farming is a difficult task. Hydroponic techniques utilizing the IoT show to deliver the finest outcomes, despite the usage of various artificial culture methods. Though, the usage of smart communication technologies and IoT exposes environments for smart farming to a wide range of cybersecurity risks and weaknesses. However, the adoption of intelligence-based controlling algorithms in the agricultural industry is a good use of current technical advancements to address these issues. This paper presented a secured framework for smart farming in hydroponics system. The proposed architecture is characterized into four-layer IoT based framework, sensor, communication, fog and cloud layer. Data analytics is performed using supervised machine learning techniques with intelligent and precise management and is applied at the fog layer for efficient computation over the cloud layer. The data security over channel is protected by using Blockchain Technology. The experimental results are evaluated and analyzed for several statistical parameters in order to improve the system efficacy.

The Effect of Teamwork and Supervision On Employee Performance (Survey of Production Department Employee at CV. Sukahati Pratama Tasikmalaya)

This study aims to determine “The Effect of Teamwork and Supervision on Employee Performance in the Production Department of CV. Sukahati Pratama Tasikmalaya”. The population in this study amounted to 260 people and the sample used in this study were 43 people in the production division. This research method is quantitative using multiple linear regression. The result of this study are that teamwork and simultaneous supervision can have a significant effect on the performance of production employees at CV. Sukahati Pratama Tasikmalaya. Partially teamwork has no significant effect on employee performance in the production section of CV. Sukahati Pratama Tasikmalaya and Supervision partially have a significant effect on the perfoemance of employees in the production section of CV. Sukahati Pratama Tasikmalaya

Federated Learning with Research Prototypes: Application to Multi-Center MRI-based Detection of Prostate Cancer with Diverse Histopathology.

Early prostate cancer detection and staging from MRI is extremely challenging for both radiologists and deep learning algorithms, but the potential to learn from large and diverse datasets remains a promising avenue to increase their performance within and across institutions. To enable this for prototype-stage algorithms, where the majority of existing research remains, we introduce a flexible federated learning framework for cross-site training, validation, and evaluation of custom deep learning prostate cancer detection algorithms. We introduce an abstraction of prostate cancer groundtruth that represents diverse annotation and histopathology data. We maximize use of this groundtruth if and when they are available using UCNet, a custom 3D UNet that enables simultaneous supervision of pixel-wise, region-wise, and gland-wise classification. We leverage these modules to perform cross-site federated training using 1400+ heterogeneous multi-parameteric prostate MRI exams from two University hospitals. We observe a positive result, with significant improvements in cross-site generalization performance with negligible intra-site performance degradation for both lesion segmentation and per-lesion binary classification of clinically-significant prostate cancer. Cross-site lesion segmentation performance intersection-over-union (IoU) improved by 100%, while cross-site lesion classification performance overall accuracy improved by 9.5-14.8%, depending on the optimal checkpoint selected by each site. Federated learning can improve the generalization performance of prostate cancer detection models across institutions while protecting patient health information and institution-specific code and data. However, even more data and participating institutions are likely required to improve the absolute performance of prostate cancer classification models. To enable adoption of federated learning with limited re-engineering of federated components, we open-source our FLtools system at https://federated.ucsf.edu, including examples that can be easily adapted to other medical imaging deep learning projects.

Die von Pflegenden unterschiedlicher Pflegeeinrichtungen wahrgenommene Belastung bei der Arbeit

The perceived workload of nurses belonging to different care facilities Aim: The study aimed to determine the workload of nurses working in outpatient care, inpatient long-term care and care in a hospital or rehabilitation facility. Of interest were the frequency of occurrence of different workload characteristics and the identification of workload characteristics in which the facilities differ from each other. The study used data from the 2018 BIBB/BAuA Employment Survey, from which 17 items were selected. The items belong to one of the following categories: work content, work organisation, social relationships and work environment. Methods: The mean values show that “good cooperation with colleagues” and “help or support from colleagues and the direct supervisor” are rated overall as occurring frequently in all three care facilities. The items “strong deadline or performance pressure”, “constantly recurring work processes”, “simultaneous supervision of different tasks”, the need to “work quickly”, “working while standing up”, “lifting and carrying of heavy loads” and the “occurrence of emotionally stressful situations” were also rated as occurring frequently. Variance analyses were then conducted and with a grouping factor (type of care facility) and the size effect measure was calculated omega-squared. Results: The item “disturbances and interruptions at work” gave the highest omega square of 0.146, indicating a moderate effect size. The other items resulted in small effect sizes. A discriminance analysis shows that the item “disturbances and interruptions at work” has highest relevance for the differentiation of the facilities, while the greatest differences is between “outpatient care” and “care in hospitals and rehabilitation facilities”. Conclusions: Based on the results, conclusions are drawn concerning work design measures. Keywords: workload – nurses – care facility – work design

Edge-aware object pixel-level representation tracking

Recently, there has been a trend in tracking to use more refined segmentation mask instead of coarse bounding box to represent the target object. Some trackers proposed segmentation branches based on the tracking framework and maintain real-time speed. However, those trackers use a simple FCNs structure and lack of the edge information modeling. This makes performance quite unsatisfactory. In this paper, we propose an edge-aware segmentation network, which uses the complementarity between target information and edge information to provide a more refined representation of the target. Firstly, We use the high-level features of the tracking backbone network and the correlation features of the classification branch of the tracking framework to fuse, and use the target edge and target segmentation mask for simultaneous supervision to obtain an optimized high-level feature with rough edge information and target information. Secondly, we use the optimized high-level features to guide the low-level features of the tracking backbone network to generate more refined edge features. Finally, we use the refined edge features to fuse with the target features of each layer to generate the final mask. Our approach has achieved leading performance on recent pixel-wise object tracking benchmark VOT2020 and segmentation datasets DAVIS2016 and DAVIS2017 while running on 47 fps. Code is available at https://github.com/TJUMMG/EATtracker.

An Analysis of the Effect of Personal Protective Equipment (PPE) Training Based on the Information-Motivation-Behavior Skills Model in the Practice of COVID-19 PPE Application.

ObjectiveThe aim of this study is to improve the effectiveness of training in putting on and removing personal protective equipment (PPE) during COVID-19.MethodsAn information–motivation–behavioral skills (IMB) model intervention team was established with the adoption of the IMB model to intervene in putting on and removing PPE by medical staff during COVID-19. Specifically, the information intervention was strengthened through the formulation of the hospital manual for PPE application. In the present study’s five-stage motivational interview, the personal motivation and social motivation of medical staff were deeply understood, helping the medical staff to improve their belief in the importance of correct PPE application and to establish the correct attitude toward PPE application. In terms of behavioral skills, there are numerous issues that could interfere with the establishment of proper PPE application, including material supply, double duty, simultaneous supervision of entering and leaving, continuous supervision, video supervision, and nosocomial infection inspection. The scores relating to PPE application knowledge and self-efficacy as well as the PPE usage qualification rate were calculated in the control group and the IMB intervention group and subsequently compared.ResultsFor the control group and the IMB intervention group, the scores for PPE application knowledge were 87.78 ± 10.46 and 95.56 ± 9.06 points, respectively. For self-efficacy, the scores were 25.19 ± 0.97 and 33.79 ± 2.05 points, and the PPE usage qualification rates were 64.8% and 90.0%, respectively. The differences in all the scores were statistically significant between the two groups.ConclusionThe application of the IMB model could improve the relevant knowledge relating to PPE application, strengthen the belief in the importance of and motivation for correct PPE application, improve the qualification rate for PPE application, and provide a theoretical and practical basis for reducing the occurrence of nosocomial infection.

Islamic Education Institution Programs That Address the Psychosocial Crises of Stude

Islamic education institutions must have programs that can answer the psychosocial crises of students. In such institutions, these programs are arranged based on Islamic paradigms and values. Furthermore, these programs are operationally supported by the availability and capacity of teachers, the facilities and infrastructure, education funding, curriculum structure, learning strategies, educational supervision, counselling guidance, and family or community support. The purpose of this study was to investigate the programs of Islamic education institutions in overcoming the psychosocial crises of students. The author conducted a literature review. The results indicated that the main strength of Islamic education institutions in implementing programs to overcome the psychosocial crises of students is a comprehensive understanding of the psychological growth and development of students from the perspective of Islamic paradigms and values. Besides, this program must be supported by teachers who are skilled in implementing counselling guidance, with simultaneous supervision of educational institutions, and parental or family support. The programs used in addressing the psychosocial crises of students in Islamic educational institutions focus on good advice (mau’izhah hasanah), exemplary behavior (uswatun hasanah), practice to do one’s best (ihsan), do good earlier (fastabiqul khairat), help each other in doing good (ta’awun), sholat and du‘a. Based on the results of this study, it can be concluded that Islamic education institutions that have programs that answer the psychosocial problems of students will continue to exist and succeed in preparing tough generations in the future, especially in crises.
 Keywords: Islamic education institutions, psychosocial crisis, students

Система контролю та нагляду над спеціальними службами США (кінець ХХ – початок ХХІ ст.)

The experience of organizing and exercising control and supervision over the US Special Services under the conditions of challenges and threats to national security, defense and interests of the state at the end of the XX – beginning of the XXI century is analyzed and generalized. It has been established that the US Special Services are within the limits and possibilities clearly outlined by national legislation under the close supervision and control of government institutions and the public defined by it. Such conditions allow them to professionally perform the tasks assigned to them within the framework of the legislative field of the state, allied and international obligations, respect for human rights and freedoms. A specific feature of the functioning of the system of control and supervision over US Special Services is a clear division of areas of its implementation by independent branches of government with simultaneous supervision over them and Special Services by public organizations and independent institutions. Somewhat more in terms of the number and scope of surveillance and control measures over the Special Services from other branches of government belongs to its executive branch – the president and the government. Extremely large control powers have been vested in US law to the Director of National Intelligence (DNI), that in effect and scope is the second official over Special Services after the country’s president. The role and place in the structure of the US Special Services of the Inspector General, who is appointed by the President, is unusual for Special Services of other countries, who subordinated and reports only to him. He is a member of DNI Directorate staff and conducts independent investigations, audit, inspections and special reviews of programs and activities of intelligence community (IC), the implementation of which is organized, lead and controlled by its head – the Director of National Intelligence. It draws attention, despite the constant terrorist threats and challenges to US security, the principled approach of independent institutions, organizations and the public to the concern for compliance with human rights and freedoms by Special Services in the performance of professional tasks both, within the country and abroad.

Metaheuristics for the multi-task simultaneous supervision dual resource-constrained scheduling problem

This comprehensive study develops advantageous optimization methods to solve a nascent problem, namely multi-task simultaneous supervision dual resource-constrained (MTSSDRC) scheduling. MTSSDRC is a complex problem that deals with machine assignment, job sequencing, operator allocation, and task sequencing. Setup and unloading must be scheduled to operators, and they are allowed to leave machines while processing jobs. Earlier research on MTSSDRC developed a permutation-based genetic algorithm (PGA) with a specific decoding scheme, namely DSE, to solve the problem. Many previous studies succeed in solving scheduling problems by modifying well-known metaheuristic techniques. Therefore, we are inspired by this to explore further modifications to particular metaheuristics. The first contribution of the present study lies in the development of new decoding schemes that can perform better than the existing option. Five new decoding schemes are considered. Two of those schemes, namely DS2 and DS4, perform significantly better than DSE, reaching 6% relative deviation. DS4 is superior in terms of solution quality, but DS2 can run eight times faster. Another contribution is the development of six modified metaheuristics that are implemented for the MTSSDRC problem: tabu search, simulated annealing, particle swarm optimization, bees algorithm (BA), artificial bee colony, and grey wolf optimization. The performance of these metaheuristics is compared with that of the PGA. The results show that the PGA and BA are consistently superior for medium- and large-sized problems. The BA is more promising in terms of solution quality, but the PGA is faster.

NSGA-II variants for solving a social-conscious dual resource-constrained scheduling problem

This present study compares various non-dominated sorting genetic algorithm II (NSGA-II) variants to deal with multi-task simultaneous supervision dual resource-constrained (MTSSDRC) scheduling to minimize the makespan and workload unbalance among operators. MTSSDRC is a complex problem that needs to integrate two types of scheduling, i.e., job sequencing on the machines and task sequencing, which includes setup, unloading, and moving, by the operators. Since there are two resources, one may be busier than the other. Task sequencing should be prioritized if the operator is very busy, otherwise, we should accentuate the job sequencing. The existing NSGA-II variant prioritizes the machine assignment over the operator. Therefore, its performance is not so well when the operator-to-machine ratio is small. Thus, this proposed research develops two new NSGA-II variants identified by their modified decoding schemes. They posit the operator more important or at least equal to the machine. To the best of our knowledge, this research is the first to analyze MTSDDRC based on the operator-to-machine ratio. The essential finding insists that each variant fits the specific ratio. The new ones are promising for cases with a ratio ⩽0.5. Otherwise, the existing variant is still recommended. Besides, one of the new decoding schemes performs well for all ratio, but not the best.

Exploration of Work Attributes in the Synergy of Institutions to Improve the Quid Pro Quo of Tourism

Importance Performance analysis (IPA) provides a useful facility to test the institutional synergy concept among tourism stakeholders. This research has a purpose to explore the perception of tourism stakeholders concerning the attributes in the value of importance and performance in tourism institutions to increase quid pro quo for the community. This study was conducted in sub-districts that have potential migrant or Indonesian Migrant Worker populations in Malang District. Samples of this research are tourism stakeholders who manage tourist attraction in productive migrant villages. They are tourism activist groups as tourism actors in the community, village government work units, and Perusahaan Daerah Jasa Yasa (Jasa Yasa Regional Company) as the manager of the tourism. The analytical tool used to measure the level of performance and importance in the synergy attributes is the Importance Performance analysis (IPA). The results of this study show the attributes of synergy between tourism stakeholder institutions have the following distribution: Environmental Changes attribute falls in Quadrant I; attributes of Continuous Coordination, Simultaneous Responsibility, Effective Communication, & Simultaneous Supervision fall in Quadrant II; Simultaneous Policy and Direct Relationship attributes fall in Quadrant III; and Obvious Purpose attributes falls in Quadrant IV.

Divide y vencerás: Efectos de dos intervenciones para el aprendizaje interactivo en grupos grandes de estudiantes sobre la percepción de la calidad del ambiente de aprendizaje

IntroductionLittle is known on the effect of different forms of division of a large group of students for the interactive discussion of cases, on the quality of the learning environment. We aim to compare two types of division in the face-to-face component of an inverted classroom in surgery. MethodsFor eighteen weeks, Group-1 was divided into eight small groups within the same physical classroom, under the simultaneous supervision of four tutors. Group-2 was divided into eight small groups distributed in four independent physical classrooms (2 groups/classroom), under the supervision of one tutor in each classroom. The quality of the learning environment was evaluated with the DREEM questionnaire. The effects of each division on the global DREEM score and its domains were evaluated with the d (Cohen) test. ResultsThe overall DREEM score was: 145.01±2.17 (Group-1) versus 131.46±18.48 (Group-2) (p<0.05). The magnitude of the effect of division of the Group-1 on the DREEM score was d=0.66. All DREEM domains were superior in Group-1 (p<0.05), as well as the effects on the quality of the environment. ConclusionsThe effects on the learning environment are greater when a large group is divided into small groups that are supervised by multiple tutors in the same physical classroom, compared with a large group that is divided into small groups that are supervised by a single tutor in separate classrooms.

Control System (CS) and Data Acquisition (DAQ) architecture for the radiation background monitoring of a Personnel Safety System in the ATLAS cavern

EDUSAFE is a 4-year Marie Curie ITN project, which focuses on research into the use of Virtual Reality (VR) and Augmented Reality (AR) during planned and emergency maintenance in extreme environments of high radiation background (HEP experiments, nuclear installations, space, deep sea, etc.) The scientific objective of this project is research into advanced VR and AR technologies for a personnel safety system platform, including features, methods and tools. Current technology is not efficient because of significant time-lag in communication and data transmission, missing multi-input interfaces, and simultaneous supervision of multiple workers who are working in the extreme high radiation background environment. The aim is to technically advance and combine several technologies and integrate them as integral part of a personnel safety system to improve safety, maintain availability, reduce errors and decrease the time needed for scheduled or sudden interventions. The research challenges lie in the development of real-time (time-lags less than human interaction speed) data-transmission, instantaneous analysis of data coming from different inputs (vision, sound, touch, buttons), interaction with multiple on-site users, complex interfaces, portability and wearability. The result is an integrated wearable VR/AR system and Control System which can be implemented and tested as a prototype. The LHC at CERN and its existing Personnel Safety System, requirements and protocols will be used as a test and demonstration platform. In this article the progress of the project will be presented and especially the major contribution of the NTUA team in developing and optimizing the Control System (CS) and the Data Acquisition System (DAQ).

Simultaneous supervision by microscope of endoscope-assisted microsurgery via presigmoid retrolabyrinthine approach: A pilot study

ObjectiveTo examine the impact of integrated hybrid operating rooms for endoscope-assisted microsurgery using the presigmoid retrolabyrinthine (RL) approach, and to determine the value of simultaneous supervision of skull base endoscopic procedures by microscope. Material and methodsWe retrospectively reviewed endoscope-assisted surgery using the RL approach at our institution between September 2013 and January 2017. The simultaneous supervision of endoscopic procedures by microscope was realized using the integrated hybrid system. Intra- or postoperative complications and surgical outcomes were analyzed. All patients were followed for at least 1 year. ResultsIn total, 32 patients were studied: 4 vestibular schwannomas, 5 cholesteatomas, 8 hemifacial spasms, 5 glossopharyngeal neuralgias, and 10 Ménière's disease. In patients with vestibular schwannoma or cholesteatoma, complete removal was performed in all patients. In patients with Ménière's disease, hemifacial spasm or glossopharyngeal neuralgia, satisfactory symptom relief was achieved in all patients. Two (6.3%) patients had hearing loss after surgery which did not recover. One (3.1%) patient with vestibular schwannoma had mild facial palsy (HB III) at 2 weeks after the operation and recovered to near normal facial nerve function (HB II) at 1 year after surgery. No permanent or transient dysfunction of the trigeminal nerve or the lower cranial nerves was observed during follow-up. No complications such as cerebrospinal fluid (CSF) leakage or meningitis were observed. ConclusionThe endoscope provided a clearer and larger view, which solved the limitations of surgery using the RL approach. Endoscopic surgery under simultaneous supervision by microscope was safe and efficient in hearing preservation as well as in preservation of facial nerve function. An integrated operation room provided better support and the ability to switch quickly between these various complex devices.

Augmented and virtual reality based monitoring and safety system: A prototype IoT platform

This paper presents an Augmented and Virtual Reality (AR/VR) based IoT prototype system. Performing maintenance tasks in a complex environment is quite challenging and difficult due to complex, and possibly, underground facilities, uneasy access, human factors, heavy machineries, etc. Current technology is not acceptable because of significant delays in communication and data transmission, missing multi-input interfaces, and simultaneous supervision of multiple workers who are working in the extreme environment. The aim is to technically advance and combine several technologies and integrate them as integral part of a personnel safety system to improve safety, maintain availability, reduce errors and decrease the time needed for scheduled or ad hoc interventions. We emphasize on the aspects that were made “feasible” on the worker's side due to the equipment used (mobile computing equipment). We present that the demanding tasks that previously were simply undertaken on the fixed infrastructure are now possible on the mobile end. The research challenges lie in the development of real-time data-transmission, instantaneous analysis of data coming from different inputs, local intelligence in low power embedded systems, interaction with multiple on-site users, complex user interfaces, portability and wearability. This work is part EDUSAFE, a Marie Curie ITN (Initial Training Network) project focusing on research into the use of Augmented and Virtual Reality (AR/VR) during planned and ad hoc maintenance in extreme work environments.

Improvement of Supervision Schedules for Protective Systems

Improvement of supervision schedule is considered for protective-systems of multiple components. Each component is periodically supervised. Our improvement procedure consists of two steps. 1) Determine the time length of supervision and duration of successive supervisions which maximize the minimum point availability for simultaneous supervision schedule where all components are supervised simultaneously. 2) Improve the supervision schedule of Step 1 by constructing a staggered supervision schedule. In this schedule components are divided into subgroups, and supervisions of subgroups are staggered while components in the same subgroup are supervised simultaneously. A systematic method is given to optimize allocating components into subgroups for a specified number of subgroups and staggering of supervisions. An example illustrates the method.