Schedule Quality Research Articles

Horizontal Bullwhip Effect - Empirical Insights into the System Dynamics of Automotive Supply Networks

As a result of a conceptual simulation study proposed by Gruchmann and Rebs (2018), the bullwhip effect in automotive supply chains is not just detectable on a vertical supply chain level under demand uncertainties, but also on a horizontal supply chain level when production risks are present. Hence, it is important to validate these results by real-life business data to gain further empirical insights into the scheduling dynamics of such networks. To measure schedule instability in automotive call-off systems, the German association of the automotive industry (VDA) proposes a set of key measures to assess schedule quality and stability (VDA guideline 5009). For this study, the key figure forecast quality (FQ) is used to analyze demand information collected from a 1st tier supplier providing components to several original equipment manufacturers (OEMs) in Europe in a period up to four months. In this context, the VDA recommends that schedule instability should decrease when moving from a long-term to a short-term planning horizon. However, the results of the analysis indicate that forecast instability increases shortly before dispatching the required parts leading to dependent requirements variations (DRVs). To the best of our knowledge, none of the existing studies addressed a horizontal bullwhip effect empirically so far. Hence, the present study intends to contribute to theory and practice by providing theoretical and managerial insights on the dynamics of the horizontal bullwhip effect.

System Dynamics Approach to Mitigating Skilled Labour Shortages in the Construction Industry: A South Africa Context

Skilled labour shortage in construction industry is a major challenge in South Africa. Therefore, the objective of the study is to assess the factors that cause skilled labour shortage, its consequent effects on the construction industries and how the scenario can be improved. The study was conducted by considering construction industry in the Eastern Cape of South Africa and using a survey research method and conceptual System Dynamics (SD) modelling. Findings reveals that investment, wage challenges, talent management, work environment, training, experience, and Government policy are the important challenges for the skilled labour shortage. Inadequacy of skilled labour considerably impacts the quality of work, productivity, and scheduling. The causal loop diagrams show that enhancement in investment in the labour wages will strengthen the availability of skilled labourers leading to higher productivity, and vice versa. Talent management based on appropriate recruitment and retention policy, staff development programmes and investment in these aspects will augment the skilled labour pool. Also, a better work environment through a policy of health and safety, investment in working condition and supported by Government policy will reduce the attrition of the labourer because of job dissatisfaction, which consequently will reduce the skilled labour shortage in the industry.

Measuring Industrial Health Using a Diminished Quality of Life Instrument

Historically, the focus of industrial health and safety (H&S) has been on safety and accident avoidance with relatively less attention to long-term occupational health other than via health monitoring and surveillance. The difficulty is the multiple overlapping health consequences that are difficult to separate, measure, and attribute to a source. Furthermore, many health problems occur later, not immediately on exposure, and may be cumulative. Consequently, it is difficult to conclusively identify the cause. Workers may lack knowledge of long-term consequences, and thus not use protective systems effectively. Compounding this is the lack of instruments and methodologies to measure exposure to harm. Historically, the existing risk methodologies for calculating safety risk are based on the construct of consequence and likelihood. However, this may not be appropriate for health, especially for the long-term harm, as both the consequence and likelihood may be indeterminate. This paper develops an instrument to measure the health component of workplace H&S. This is achieved by adapting the established World Health Organization Disability Assessment Schedule (WHODAS) quality of life score to workplace health. Specifically, the method is to identify the likelihood of an exposure incident arising (as estimated by engineering technologists and H&S officers), followed by evaluation of the biological harm consequences. Those consequences are then scored by using the WHODAS 12-item inventory. The result is an assessment of the Diminished Quality of Life (DQL) associated with a workplace hazard. This may then be used to manage the minimization of harm, exposure monitoring, and the design of safe systems of work.

Mixed-integer programming models for optimal constellation scheduling given cloud cover uncertainty

We consider the problem of scheduling observations on a constellation of remote sensors, to maximize the aggregate quality of the collections obtained. While automated tools exist to schedule remote sensors, they are often based on heuristic scheduling techniques, which typically fail to provide bounds on the quality of the resultant schedules. To address this issue, we first introduce a novel deterministic mixed-integer programming (MIP) model for scheduling a constellation of one to n satellites, which relies on extensive pre-computations associated with orbital propagators and sensor collection simulators to mitigate model size and complexity. Our MIP model captures realistic and complex constellation-target geometries, with solutions providing optimality guarantees. We then extend our base deterministic MIP model to obtain two-stage and three-stage stochastic MIP models that proactively schedule to maximize expected collection quality across a set of scenarios representing cloud cover uncertainty. Our experimental results on instances of one and two satellites demonstrate that our stochastic MIP models yield significantly improved collection quality relative to our base deterministic MIP model. We further demonstrate that commercial off-the-shelf MIP solvers can produce provably optimal or near-optimal schedules from these models in time frames suitable for sensor operations.

A reinforcement learning based approach for multi-projects scheduling in cloud manufacturing

This paper discussed the multi-projects scheduling problem in Cloud Manufacturing system, where each of the projects is a set of interrelated tasks, and these projects need to be scheduled timely and carefully. However, scheduling massive projects can be challenging due to the uneven distribution of the services and the uncertain arrival of projects. Therefore, we (1) established a dual-objectives optimisation model to minimise both the total makespan and the logistical distance; (2) proposed a Reinforcement Learning based Assigning Policy (RLAP) approach to obtain non-dominated solution set; (3) designed a dynamic state representing an algorithm for agents to determine their decision environment when using RLAP. Experiment results show that RLAP can adjust the distribution of service load according to the nearby tasks, and the schedule quality is improved by and compared with NSGA-II and Q-learning, respectively. Besides, the RLAP method has the ability to schedule stochastically arriving projects.

Employee scheduling with short demand perturbations and extensible shifts

Employee scheduling is an important activity in the service industry as it has a significant impact on costs, sales, and profitability. While a large amount of mathematical models and methods have been established in the literature for finding optimized schedules, only few propose methods for practically relevant problem settings including uncertainty, which is an important aspect of employee scheduling in the service industry.This article contributes to narrowing this research gap by addressing a practice-inspired employee scheduling problem arising in retail stores. In particular, the scheduling problem under study includes short demand perturbations, potentially leading to an increase of the demand in some time intervals, and the possibility of assigning overtime work by extending shifts to cope with a lack of employees in real-time. The goal is to find an initial schedule minimizing the sum of demand fulfillment and employee preference-related costs, where each cost term is expressed as a convex function of an appropriate variable. The cost of a schedule is evaluated using a simulation-based approach reproducing the materialization of demand perturbations and shift extensions.To find reasonably good robust employee schedules within a relatively short computation time for practical-sized instances, we propose two integer programming models taking into account the demand uncertainty and shift extension possibilities in different ways. In the first model, a bonus term is assigned in the objective function for shifts that can cover some perturbation demand within their extension period, while in the second model, a potential demand is derived from the perturbations and its under-coverage is penalized. Extensive computational results on retail store instances reveal that the two proposed robust models improve the schedule quality significantly when compared with a basic non-robust model. This result further underpins the value of including uncertainty information and recourse actions in the employee scheduling activity.

Using preferred fluids and different reward schedules to motivate rhesus macaques (Macaca mulatta) in cognitive tasks.

Rhesus macaques (Macaca mulatta) used in behavioural neuroscience are often required to complete cognitively complex tasks, for which a high level of motivation is essential. To induce motivation, researchers may implement fluid-restriction protocols, whereby freely available water is limited, such that fluid can be used as a reward in the laboratory. A variety of different rewards and schedules are used, but there exists a lack of data assessing their effectiveness. In this study, we aimed to quantify fluid preference in rhesus macaques and to use these preferences to compare the motivational quality of different reward schedules: the monkey's previous reward (i.e. the fluid used to reward them in past studies), their new preferred reward, a variable schedule of previous and preferred reward, and a choice between the previous and preferred rewards. We found that it may be possible to reduce the level of restriction if an adequately motivating preferred reward is identified, but that this is dependent on the animal. Each monkey responded differently to both the fluid-preference assessments and to the different reward schedules. As such, monkeys should not be subject to 'blanket' protocols but should be assessed individually to maintain adequate scientific data collection at the least severe level of fluid restriction.

PHP341 - ARE THERE ENOUGH REGULATIONS TO COMBAT THE POOR QUALITY POVIDONE-IODINE IN EGYPT

Iodophor antiseptic solutions are currently used in healthcare for many purposes, including skin antisepsis before surgery and venipuncture, irrigation of wounds and ulcers. Harmful adverse effects from the use of the poor-quality povidone-iodine have been documented in Egypt. Contamination of the implicated povidone-iodine occurred at the site of manufacture. The objective of this study is to discuss and set recommendations to combat the poor-quality povidone-iodine in Egypt. A focus group of decision makers that included academic experts with experience in health economics, clinical pharmacology, and infection control were invited by a research unit to develop a set of recommendations taking into account current practices by using a Quasi Delphi method. Poor-quality products may contain incorrect amounts or even no active ingredients at all, as well as products that are inadequate due to poor compliance to conventional quality standards. This can subject the population to more severe and prolonged illness, resulting in additional costs to payers. A set of recommendations can combat the distribution of poor-quality povidone-iodine in Egypt; including adhering to good manufacturing practices and taking appropriate measures, such as scheduled quality control checks of finished product , applying a dispenser with safety sealing mechanism to prevent any contamination, incentivizing retailers to identify and report falsified poor quality products, and implementing efficient import/export control systems. These recommendations can improve the health outcomes of population subjected to the use of these products. There is still an urgent need for a collective response by the decision makers, regulatory bodies, and pharmaceutical companies to enhance research and develop funding, such as for new track-and-trace field devices.

The influence of algorithms for basic-schedule generation on the performance of predictive and reactive schedules

Lately, a great deal of effort has been spent developing methods to generate robust schedules. The Multi-Objective Immune Algorithm (MOIA) is one of the methods dealing with an uncertainty [1]. The basic schedules, obtained by the MOIA, are modified using the rule of the Minimal Impact of Disturbed Operation on the Schedule (MIDOS) in order to generate predictive schedules. If the effect of a disruption is too large, in order to generate reactive schedules, the rule of the Minimal Impact of Rescheduled Operation on the Schedule (MIROS) is applied. This paper is the continuation of the searching process for an algorithm which achieves good quality basic schedules that influence on the quality of predictive and reactive schedules. In [2,3], the two immune algorithms are compared, the MOIA and Clonal Selection Algorithm (CSA) when investigating the influence of basic schedules on the obtainment of stable and robust schedules with the application of the MIDOS and MIROS. The two algorithms are applied for a multi criteria job shop scheduling problem. In this paper, the genetic algorithm (GA) is applied for the same scheduling problem and the achieved schedules are compared.

Parametric analysis of the quality of single preemption schedules on three uniform parallel machines

For a scheduling problem to minimize the makespan on three uniform parallel machines we present a parametric analysis of the quality of a schedule with at most one preemption compared to the global optimal schedule with any number of preemptions. A tight bound is derived as a function of the relative speeds of the machines, provided that two of the machines have the same speed.

Design of Production Management System in ERP of Coal Chemical Industry

A set of ERP production management system is to be designed for coal chemical enterprises. With the coal chemical enterprise A as an example, it will be designed according to the actual needs of the enterprise A. after the application of ERP management system, the enterprise A is able to comprehensively manage and handle multiple production plans, master real-time production schedule and query production quality and cost, achieving remarkable results. The design of ERP production management system is important to the fine development of coal chemical industry and can effectively improve the internal management level of coal chemical enterprises.

Scheduling quality of precise form sets which consist of tasks of circular type in GRID systems

Users’ demand in computer power and rise of technology favour the arrival of Grid systems. The quality of Grid systems’ performance depends on computer and time resources scheduling. Grid systems with a centralized structure of the scheduling system and user’s task are modeled by resource quadrant and re-source rectangle accordingly. A Non-Euclidean heuristic measure, which takes into consideration both the area and the form of an occupied resource region, is used to estimate scheduling quality of heuristic algorithms. The authors use sets, which are induced by the elements of square squaring, as an example of studying the adapt-ability of a level polynomial algorithm with an excess and the one with minimal deviation.

Survey of the prevalence and methodology of quality assurance for B-mode ultrasound image quality among veterinary sonographers.

Image quality in B-mode ultrasound is important as it reflects the diagnostic accuracy and diagnostic information provided during clinical scanning. Quality assurance programs for B-mode ultrasound systems/components are comprised of initial quality acceptance testing and subsequent regularly scheduled quality control testing. The importance of quality assurance programs for B-mode ultrasound image quality using ultrasound phantoms is well documented in the human medical and medical physics literature. The purpose of this prospective, cross-sectional, survey study was to determine the prevalence and methodology of quality acceptance testing and quality control testing of image quality for ultrasound system/components among veterinary sonographers. An online electronic survey was sent to 1497 members of veterinary imaging organizations: the American College of Veterinary Radiology, the Veterinary Ultrasound Society, and the European Association of Veterinary Diagnostic Imaging, and a total of 167 responses were received. The results showed that the percentages of veterinary sonographers performing quality acceptance testing and quality control testing are 42% (64/151; 95% confidence interval 34-52%) and 26% (40/156: 95% confidence interval 19-33%) respectively. Of the respondents who claimed to have quality acceptance testing or quality control testing of image quality in place for their ultrasound system/components, 0% have performed quality acceptance testing or quality control testing correctly (quality acceptance testing 95% confidence interval: 0-6%, quality control testing 95% confidence interval: 0-11%). Further education and guidelines are recommended for veterinary sonographers in the area of quality acceptance testing and quality control testing for B-mode ultrasound equipment/components.

Maintenance, shutdown and production scheduling in semiconductor robotic cells

Our approach is the first to study simultaneous scheduling of preventive maintenance, shutdowns and production for robotic cells in semiconductor manufacturing. It hereby exploits the frequent periods of overcapacity in semiconductor manufacturing to reduce wear and tear. In contrast to existing approaches, our scheduling approach is able to deal with different preventive-maintenance types. We borrow the Resource Task Network representation from the process-industry domain to represent our problem and facilitate its formulation as a mathematical model. In addition, we develop efficiency-improving constraints based on the characteristics of the preventive-maintenance activities. In numerical tests based on industry data, we show that the model generates high-quality schedules even without applying the inequalities, although the optimality gap is reduced only when including inequalities. We furthermore assess the trade-off between shutdowns and batch lead times. We compare our model’s schedule quality to (i) the simple industry practice of shutting down chambers permanently to reduce wear and tear and (ii) an approach that schedules maintenance and production sequentially. The numerical tests yield the following managerial insights. First, integrating maintenance and production scheduling has substantial advantages. Second, the practice of shutting equipment down permanently diminishes scheduling flexibility and solution quality. Third, shutdowns scheduling must also consider the impact on batch waiting times.

Compassionate care intervention for hospital nursing teams caring for older people: a pilot cluster randomised controlled trial

ObjectiveCompassionate care continues to be a focus for national and international attention, but the existing evidence base lacks the experimental methodology necessary to guide the selection of effective interventions for...

Announcing the 2018 Processes Travel Award for Post-Doctoral Fellows and Ph.D. Students

first_page settings Order Article Reprints Font Type: Arial Georgia Verdana Font Size: Aa Aa Aa Line Spacing:    Column Width:    Background: Open AccessEditorial Announcing the 2018 Processes Travel Award for Post-Doctoral Fellows and Ph.D. Students by Michael A. Henson Department of Chemical Engineering and Institute for Applied Life Sciences, 240 Thatcher Way, University of Massachusetts, Amherst, MA 01003, USA Processes 2018, 6(1), 1; https://doi.org/10.3390/pr6010001 Received: 20 December 2017 / Revised: 20 December 2017 / Accepted: 22 December 2017 / Published: 1 January 2018 Download Download PDF Download PDF with Cover Download XML Download Epub Versions Notes With the goal of promoting the development of early career investigators in the fields of chemical process and biological systems engineering, Processes welcomed applications for the 2018 Processes Travel Award for post-doctoral fellows and Ph.D. students. We received 72 applications for the award, and the overall quality of the applications was outstanding. On behalf of the Editors of Processes, I am pleased to announce the winner of the inaugural Processes Travel Award for 2018.The Processes Travel Award has been granted to Mr. Dhruv Gupta, a Ph.D. candidate in Christos Maravelias’ laboratory at University of Wisconsin-Madison. He will receive 800 CHF to help support travel to present his research at the Process Systems Engineering conference (PSE 2018) in San Diego, CA, USA. His presentation is entitled “General Mixed-Integer Programming State-Space Model for Online Scheduling.” Mr. Gupta obtained his B.S. degree in Chemical Engineering at IIT-Bombay, graduating among the top students in his class. He joined Christos Maravelias’ research group in November 2013 and is working towards the development of optimization methods for online chemical production (re)scheduling. He has streamlined the terminology for the new field of online scheduling, proposed a general framework for online scheduling, and showed how past methods/approaches for rescheduling fit into the novel generalized framework he has proposed. He has invented a new state-space model for online scheduling, thus alleviating many of the challenges which were earlier preventing the application of scheduling in commercial areas such as bio-manufacturing. On a fundamental level, his investigation has led to the understanding of how the design of the scheduling problem solved online (the open-loop problem), and the frequency at which it is solved, affects the quality of the actual implemented schedule (the closed-loop schedule). His ultimate goal is to find the best “online scheduling algorithm.” He already has three very high-quality first author publications to his credit and is preparing more manuscripts. The Editor, Managing Editors, and Editorial Board Members congratulate Mr. Dhruv Gupta on winning the 2018 Processes Travel Award and we are grateful to MDPI for their generous support of the award this year and in the future. © 2018 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Share and Cite MDPI and ACS Style Henson, M.A. Announcing the 2018 Processes Travel Award for Post-Doctoral Fellows and Ph.D. Students. Processes 2018, 6, 1. https://doi.org/10.3390/pr6010001 AMA Style Henson MA. Announcing the 2018 Processes Travel Award for Post-Doctoral Fellows and Ph.D. Students. Processes. 2018; 6(1):1. https://doi.org/10.3390/pr6010001 Chicago/Turabian Style Henson, Michael A. 2018. "Announcing the 2018 Processes Travel Award for Post-Doctoral Fellows and Ph.D. Students" Processes 6, no. 1: 1. https://doi.org/10.3390/pr6010001 Find Other Styles Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here. Article Metrics No No Article Access Statistics For more information on the journal statistics, click here. Multiple requests from the same IP address are counted as one view.

Lead time prediction using machine learning algorithms: A case study by a semiconductor manufacturer

The accurate prediction of manufacturing lead times (LT) significantly influences the quality and efficiency of production planning and scheduling (PPS). Traditional planning and control methods mostly calculate average lead times, derived from historical data. This often results in the deficiency of PPS, as production planners cannot consider the variability of LT, affected by multiple criteria in today’s complex manufacturing environment. In case of semiconductor manufacturing, sophisticated LT prediction methods are needed, due to complex operations, mass production, multiple routings and demands to high process resource efficiency. To overcome these challenges, supervised machine learning (ML) approaches can be employed for LT prediction, relying on historical production data obtained from manufacturing execution systems (MES). The paper examines the use of state-of-the-art regression algorithms and their effect on increasing accuracy of LT prediction. Through a real industrial case study, a multi-criteria comparison of the methods is provided, and conclusions are drawn about the selection of features and applicability of the methods in the semiconductor industry.

Информационное обеспечение поддержки принятия решений на примере составления расписания занятий образовательной организации

This article is about a task of learning of effective use of information technologies with the decision support. The criteria for evaluating the activity of economic and social systems are systematized, their classification and areas of application of particular criteria of different nature are given. It is proposed to integrate knowledge in the field of information technologies in order to decision support on example of an actual task of scheduling lessons. The initial data are determined, the factors of the model are classified, a mathematical model is designed, its limitations are proposed. Methods for obtaining schedule quality criteria from various points of view and integral quality criterion design are presented. The limitations of possible solutions are considered and classified. Some examples of formula criteria unusability are given. The selection of optimization algorithms based on an integral criterion is substantiated. The transition from structural models of the activity of decision makers to information models of decision support systems is shown. The concept of an expert decision support is offered by an estimation of its difficultly formalized actions on change of parametric values of the system. Sets of objects of the system are compared to the essences of the information model, and its improving transformations are given. The variants of the information model with different degrees of normalization are considered; their comparative advantages and disadvantages are shown. The directions of development of the information model in the structure of the automated management system of the university are determined. As a conclusion a possibility of increasing the efficiency of the activities of complex socio-economic systems through the rational use of mathematical, information and simulation tools is proved. It is shown that this area of activity is currently promising from the point of view of the effective application of the efforts of a specialist in the field of informatics.

How does the length of day shift affect patient care on older people's wards? A mixed method study

BackgroundInternationally, studies have focused on whether shift length impacts on patient care. There are also ongoing concerns about patient care for older people in hospital. The study aim was to investigate how length of day shift affects patient care in older people’s hospital wards. Objectives1) To explore how length of day shift affects patient care in older people’s wards; 2) To explore how length of day shift affects the quality of communication between nursing staff and patients/families on older people’s wards DesignA mixed method case study. SettingsThe study was based on two older people’s wards in an acute hospital in England. One ward was piloting two, overlapping 8h day shifts for 6 months while the other ward continued with 12h day shifts. Participants and methodsQualitative interviews were conducted with 22 purposively recruited nursing staff (17 registered nurses; 5 nursing assistants). An analysis of patient discharge survey data was conducted (n=279). Twenty hours of observation of nursing staff’s interactions with patients and families was conducted, using an adapted version of the Quality of Interaction Schedule (301 interactions observed), with open fieldnotes recorded, to contextualise the observations. ResultsThere were no statistically significant differences in patient survey results, or quality of interactions, between the two wards. There were three overall themes: Effects of day shift length on patient care; Effects of day shift length on continuity of care and relationships; Effects of day shift length on communication with patients and families. Nursing staff believed that tiredness could affect care and communication but had varied views about which shift pattern was most tiring. They considered continuity of care was important, especially for older people, but had mixed views about which shift pattern best promoted care continuity. The difficulties in staffing a ward with an 8h day shift pattern, in a hospital that had a 12h day shift pattern were highlighted. Other factors that could affect patient care were noted including: ward leadership, ward acuity, use of temporary staff and their characteristics, number of consecutive shifts, skillmix and staff experience. ConclusionsThere was no conclusive evidence that length of day shift affected patient care or nursing staff communication with patients and families. Nursing staff held varied views about the effects of day shift length on patient care. There were many other factors identified that could affect patient care in older people’s wards.

Reliability, feasibility, and validity of the quality of interactions schedule (QuIS) in acute hospital care: an observational study

BackgroundResearch into relational care in hospitals will be facilitated by a focus on staff-patient interactions. The Quality of Interactions Schedule (QuIS) uses independent observers to measure the number of staff-patient interactions within a healthcare context, and to rate these interactions as ‘positive social’; ‘positive care’; ‘neutral’; ‘negative protective’; or ‘negative restrictive’. QuIS was developed as a research instrument in long term care settings and has since been used for quality improvement in acute care. Prior to this study, its use had not been standardised, and reliability and validity in acute care had not been established.MethodsIn 2014 and 2015 a three - phase study was undertaken to develop and test protocols for the use of QuIS across three acute wards within one NHS trust in England. The phases were: (1) A pilot of 16 h observation which developed implementation strategies for QuIS in this context; (2) training two observers and undertaking 16 h of paired observation to inform the development of training protocols; (3) training four nurses and two lay volunteers according to a finalised protocol followed by 36 h of paired observations to test inter-rater agreement. Additionally, patients were asked to rate interactions and to complete a shortened version of the Patient Evaluation of Emotional Care during Hospitalisation (PEECH) questionnaire.ResultsProtocols were developed for the use of QuIS in acute care. Patients experienced an average of 6.7 interactions/patient/h (n = 447 interactions). There was close agreement between observers in relation to the number of interactions observed (Intraclass correlation coefficient (ICC) = 0.97) and moderate to substantial agreement on the quality of interactions (absolute agreement 73%, kappa 0.53 to 0.62 depending on weighting scheme). There was 79% agreement (weighted kappa 0.40: P < 0.001; indicating fair agreement) between patients and observers over whether interactions were positive, negative or neutral.ConclusionsObservers using clear QuIS protocols can achieve levels of agreement that are acceptable for the use of QuIS as a research instrument. There is fair agreement between observers and patients’ rating of interactions. Further research is needed to explore the relationship between QuIS measures and reported patient experience.