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The research aims to use the latest technology, namely "Concurrent Engineering ", to redraw production and assembly lines to be more efficient and take less time in manufacturing and delivery. Which will help to earn more money, reduce the cost, achieve quality standards, and continue the production line in the assembly lines of the General Company for Mechanical Industries / Automotive Assembly Line, calculating the workstations and stages until the final production and presenting it to the customer. It was noted that there were multiple problems that led to losses on the assembly line as a result of the lack of distribution and timing of activities across the stages of the production line, causing bottlenecks in some workstations. This was reflected in a loss of about (398) minutes at a cost of about $3,900 per minute, which led to insufficient use of human or material resources (machinery and equipment). The current study presented a proposal through which the assembly line can be restructured and the implementation of some activities that are close in completion time can be synchronized, which in turn leads to reducing the total completion time from (937.5 to 772 minutes), that is, by 16.75%, in addition to maximizing working times and machine operating efficiency. And reduce wasted time at most stations. [ABSTRACT FROM AUTHOR]

Few studies have examined variability in OR utilization across weekdays. We conducted a retrospective analysis to determine OR utilization differences by day of the week and the source and financial effects of any variability. We extracted 55 months of data from a surgical data repository to calculate OR utilization, late starts, idle times, and delays for each weekday. Declines in OR utilization occurred as the week progressed and were attributed to compounding changes in late start, delay, and idle time. The average weekly cost for each OR associated with unused staffed minutes below a target OR utilization of 85% was $19,383, and the comparable lost weekly revenue was $60,256. Perioperative leaders should identify sources of OR utilization variability when developing strategies that enhance outcomes for patients, minimize costs, and maximize revenue. [ABSTRACT FROM AUTHOR]

Automated material transfer between workstations is a key feature of flexible manufacturing systems. The aim of automation is to increase the output rate while reducing the manufacturing throughput. However, machine idle time contributes significantly to the overall throughput time and cannot be completely eliminated; it can only be minimized. Accurately locating the bottleneck and synchronizing it with other assembly line equipment can help reduce throughput. The process or activity with no idle or waiting time is known as the bottleneck in a production system. In this paper, we will analyze the bottleneck in Coca-Cola's production line at Lae and provide suggestions for reducing throughput. [ABSTRACT FROM AUTHOR]

The present paper tackles the dynamic job shop scheduling problem (DJSSP), aiming to schedule a new set of jobs while minimizing the completion time of all operations. The problem is an NP-hard combinatorial optimization problem. This contribution proposes an optimal scheduling method based on the evolutionary genetic algorithm approach. The difficulty of this problem is to comprehensively find the best direction of a candidate solution while maintaining the minimum total completion time known as the makespan and denoted as Cmax. To adapt the system to changes and perform the scheduling of a new job, a local search could be an appropriate solution to fix and repair the problem by guiding the search directions following the job’s arrival. Experiment-based statistical analysis shows that the proposed model has better convergence and accuracy than state-of-the-art algorithms.

One of the common issues in production scheduling is the flow shop sequencing issue. A specific type of manufacturing process follows a predetermined linear structure in a flow shop. To solve a flow shop problem in a static workshop, the goal of this study is to determine the shortest possible total processing time (make-span) for a sequence of 'n' tasks on 'm' machines. The suggested method is based on how each work slopes as it moves from the first to the last machine. This method is contrasted with four popular heuristics (Palmer, CDS, Dannenbring, NEH). The findings of the study for 'n' x 'm' flow shop sequencing problems show that the proposed method is effective and shows a promising amount of progress when compared to the other four heuristic strategies. [ABSTRACT FROM AUTHOR]

In this paper, we address the weighted multi-objective re-entrant owshop scheduling problem considering release dates in order to minimize makespan, total completion time, total tardiness, maximum idle time, and number of tardy jobs. Each job is taken into account with deterministic processing times, and release dates. The flow-shop comprised of two workshops in whose jobs are entered to the main workshop and after the first part of the processing, they are transferred to the second workshop and after this stage, the jobs are returned to the main workshop for the last part of the processing. We model the problem by a new mixed integer programming based on formulating sum of idle time as a new concept. Moreover, a hybrid evolutionary algorithm is proposed based on some dispatching rules, ant colony optimization, and genetic algorithm. The performance of the proposed algorithm on some test instances is compared to the mixed integer linear programming model as well as the state-of-the-art algorithms called genetic algorithm, tabu search, bio-geography based optimization, and artificial bee colony. The computational experiments show that our proposed approach outperforms other algorithms and the results indicate efficiency and capability of the proposed algorithm in comparison with the traditional algorithms. [ABSTRACT FROM AUTHOR]

Interruptions are common in organizational life and last from seconds and minutes to hours and days. We rely on a quantitative abductive strategy to determine how extended work interruptions shape employees' creativity. We start by studying how surprising interruptions that cause idle time affect employees' creative performance. We do so by exploiting a natural experiment—a supply chain shortage that caused unexpected stops in production plants—to show that individuals exposed to such an interruption produce 58% more ideas than uninterrupted employees in the three weeks after the interruption. We corroborate this effect in a replication and extend it to idea quality. Investigating the effect's causes, we then show that we do not find the same effects for two other interruption types: for unexpected interruptions without idle time (i.e., intrusions), we find a negative effect on creative performance because employees forcefully disengage from their work and switch their attention to the interrupting task. For expected interruptions with idle time (i.e., planned breaks), we also find no positive effect on creative performance because employees discretionally disengage from work and focus on nonwork and leisure goals. We consider and evaluate three different theoretical explanations for our findings: attention residue, cognitive stimulation, and recovery. We end our abductive process by putting attention residue forward as the most likely explanation. Finally, we suggest three propositions based on our findings and discuss our contributions to the literature on interruptions and creativity in organizations. Funding: T. G. Schweisfurth acknowledges funding from the Tempowerk Technology Center Hamburg. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to examine the repercussions of idle time on youthful population through critically analyzing the status quo of youth unemployment in South Africa. Youth unemployment has become a major source of concern in South Africa and around the world. The unemployment challenge has thus left many young people in limbo, a state of misery, idleness, and social death. It subsequently exposed many young South African to socially immoral activities such as, inter alia, drug and alcohol use, deceit and theft. Idle time, the period people wastefully spend doing nothing productive, vehemently led many young people to perish, and ostensibly resulted into the economic stagnation in South Africa. This paper fastened its philosophical argument on the biblical aphorism that “an idle mind is the devil’s workshop”. Design/Methodology/Approach: The paper adopted a qualitative desktop-based research methodology as well as document analysis as data analysis tool. Findings: The results established that the persistent challenge of youth unemployment has pushed South Africa’s economic development into a downward spiral toward underdevelopment and vulnerability. Therefore, the country lacks a holistic approach to address idleness and unemployment, to unlock the potential of its youthful population, stimulate economic growth and development. Implications/Originality/Value: It is therefore concluded that youth unemployment has become a serious dilemma in South Africa, that it subjected majority of young people to idleness and encourages them to engage in immoral activities such as crime, making them more susceptible to the onset of drug and alcohol use. The paper recommended that the government should adopt effective mechanisms to engage unemployed youth into the economic mainstream, to enhance development and reduce idle time tragedies.

Automated material transfer between workstations is a key feature of flexible manufacturing systems. The aim of automation is to increase the output rate while reducing the manufacturing throughput. However, machine idle time contributes significantly to the overall throughput time and cannot be completely eliminated; it can only be minimized. Accurately locating the bottleneck and synchronizing it with other assembly line equipment can help reduce throughput. The process or activity with no idle or waiting time is known as the bottleneck in a production system. In this paper, we will analyze the bottleneck in Coca-Cola’s production line at Lae and provide suggestions for reducing throughput.

The job shop scheduling problem (JSP) has consistently garnered significant attention. This paper introduces an improved genetic algorithm (IGA) with dynamic neighborhood search to tackle job shop scheduling problems with the objective of minimization the makespan. An inserted operation based on idle time is introduced during the decoding phase. An improved POX crossover operator is presented. A novel mutation operation is designed for searching neighborhood solutions. A new genetic recombination strategy based on a dynamic gene bank is provided. The elite retention strategy is presented. Several benchmarks are used to evaluate the algorithm's performance, and the computational results demonstrate that IGA delivers promising and competitive outcomes for the considered JSP.

The Banbury mixing process (BMP) is to supplies the specific characteristic compounds for the tire manufacturing process. Idle time in the BMP was a problem caused by the aging process between mixing steps and the limited space for processing, measured in pallets. In this study, the resource-constrained project scheduling model (RCPS) is modified in case of the objective function and the input value of resource constraint to minimize idle time (SST). The complete minimization (Cmax) is changed from minimizing the starting time of the last job to the starting time of all jobs. In addition, the non-limited resource is defined as the input for the space capacity to reduce the idle time. As the results, the SST can provide the schedule that make less 5 time periods of idle time. Moreover, when considering the relationship between mixing and aging, aging process that is scheduled from SST starts immediately comparison to Cmax that some of aging process are not. Furthermore, the effect of the quantity of pallets was also examined. Although the non-limited resource does not make any delay to the schedule but the limited quantity is not. When pallets are limited, aging jobs were significantly impacted, with the last aging pallet being delayed. To reduce delays, it prepares an adequate supply of pallets that is close to or equal to its requirement that is defined by the non-limited resource. Further research combining the scheduling of the BMP with the tire manufacturing process and more techniques to modify RCPS are applied.

Internal combustion engines are one of the major factors of global warming and greenhouse gasses, as they emit harmful emissions such as CO2, CO, HC, and NOx. Therefore, the regulations on CO2 and other exhaust emissions for vehicles are gradually being tightened. In this study, exhaust emissions of the spark ignition engine are measured by using the portable emissions measurement system and compact exhaust gas analyzer for the vehicle used in tests carried out according to Real Driving Emission procedures to reach sustainable environmental future. The effects of the ambient temperature (AT) at the start of the engine and the time from starting the engine of the vehicle to the moment of first departure on the exhaust emissions released along the test route were investigated. By increasing the first idle time (IT), reductions in CO, THC, and NOx emissions during the test route are approximately found as 23%, 45%, and 66.5%, respectively. Better emission values are achieved during the test with the effect of increasing the AT. In the tests carried out along the determined route, it has been observed that increasing the first IT of the engine and the AT that the vehicle is waiting for reduces the emission values. [ABSTRACT FROM AUTHOR]

Idle time is a period during which employees cannot complete their work tasks for reasons beyond their control. It has previously been shown to have negative consequences for employees' performance and well-being. To shed light on the mechanisms underlying these effects, we argue based on affective events theory and action regulation theory that idle time is an event that leads to boredom. Since boredom is a negative affective experience that motivates employees to do something about their situation, it may reduce job satisfaction and increase extra-role behaviour (i.e., prosocial and counterproductive) and turnover intentions. We tested our hypotheses using a sample of 1,036 employees who participated in a five-wave longitudinal study across 12 months. Results showed that, at both the within-person and between-person levels, idle time was positively associated with boredom, which, in turn, was associated with lower job satisfaction, higher counterproductive work behaviour, and higher turnover intentions, but not with prosocial work behaviour. These associations were robust when additionally controlling for work environment features (e.g., working from home), dispositions (e.g., personality), and demographic characteristics. Thus, idle time seems to be a boring and mostly negative experience for employees. Employees and managers should organize work to avoid boredom whenever possible. [ABSTRACT FROM AUTHOR]

The classical economic growing quantity (EGQ) model is a key concept in the inventory control problems research literature. The EGQ model is commonly employed for the purpose of inventory control in the management of growing items, such as fish and farm animals, within industries such as livestock, seafood, and aviculture. The economic order quantity (EOQ) model assumes that customer demand is satisfied without interruption in each cycle; however, this assumption is not always true for some companies as they do not have continuous operations, except for item storage, during non-working times such as weekends, natural idle periods, or spare time. In this study, we extend the traditional EGQ model by incorporating the concept of working and non-working periods, resulting in the development of a new model called discontinuous economic growing quantity (DEGQ). Unlike the conventional EGQ model, the DEGQ model considers the presence of intermittent operational periods, in which the firm is actively engaged in its activities, and non-working periods, during which only storage-related operations occur. By incorporating this discontinuity, the DEGQ model provides a more accurate representation of real-world scenarios where businesses operate in a non-continuous manner, thus enhancing the effectiveness of inventory control and management strategies. The study aims to obtain the optimal number of periods in each cycle and the optimal slaughter age for the breeding items, and, subsequently, to find the optimal order size to minimize the total cost. Finally, we propose an optimal analytical procedure to determine the optimal solutions. This procedure entails finding the optimal number of periods using a closed-form equation and determining the optimal slaughter age by exhaustively searching the entire range of possible growth times. [ABSTRACT FROM AUTHOR]

The aim of this work is to substantiate the idle time evaluation of the overhead power line (OPL) according to the reliability indicators of its main elements using the probability value of the overhead power line availability factor. Statistical studies of the 17 OPL were performed to achieve this goal. The results of the statistical data processing made it possible to consider over-head lines as objects of a multiple action, and their failure and recovery flows as the primitive Poissonian flows. The calculation of the Wilcoxon and Pearson criteria confirmed the uniformi-ty of the statistical material both in terms of failure times and recovery time for all 17 studied OPL, which allowed combining the uniform statistical data into two representative samples, ac-cording to failures and recoveries, for the generalized district OPL and calculate its reliability indicators. The most significant result is the justification of applying queuing theory methods to evaluate the idle time of 6–10 kV single-chain and double-chain of overhead lines. The signifi-cance of the results obtained consists in that a simple engineering method is proposed to evalu-ate the availability factor of the overhead power line according to the reliability indicators of its main elements, which allows predicting the idle time of the overhead line for the upcoming cal-endar year of its operation. The newly obtained availability factors of the main overhead line elements can be used in the overhead power lines’ design.

Idle time at work is a phase of involuntary downtime during which employees experience that they cannot carry out their work tasks. In contrast to breaks, interruptions, procrastination, or withdrawal behavior, employees cannot work because of the absence of work-related tasks. Based on action regulation theory, we develop an integrative conceptual model on the antecedents and consequences of the subjective experience of idle time. We propose that work constraints (i.e., regulation problems) have negative effects on occupational well-being and task performance, and that these effects are mediated by subjective idle time. The strength of these effects is further assumed to be influenced by individuals' use of proactive (i.e., prevention) and adaptive (i.e., coping) strategies. Results of a supplemental qualitative study, for which we interviewed 20 employees from different occupations, provided preliminary support for the propositions. Finally, we develop theory on how individual, situational, and organizational characteristics may influence the proposed effects on and of idle time. Overall, this conceptual development paper contributes to a better theoretical understanding of idle time at work by extending its definition and applying action regulation theory to this practically important phenomenon. [ABSTRACT FROM AUTHOR]

This work presents the evaluation of the interlayer temperature (IT) with travel speed (TS) combined effect for a given wire feed speed (WFS) on operational, geometrical, and metallurgical features of thin walls with the same width deposited by wire arc additive manufacturing (WAAM) with a low alloy steel, using or not active cooling. A preliminary experimental design was carried out to define a range of IT that could prevent the molten pool from running down and, then, be used in the main experimental design. The main tests were planned and performed to find different IT and TS combinations for a given WFS capable of depositing walls with the same target effective wall width. After selecting the parameters, six walls were deposited, three under natural cooling (NC) and three under near immersion active cooling (NIAC). A more significant temperature variability along the layer length (ΔT/ΔLL) is observed in increasing IT-TS combination and under NIAC. Regardless of the cooling approach, a worse surface aspect was observed with lower IT and TS. However, NC or NIAC do not affect the wall width (effective or external) or the layer height. On the other hand, they are affected by the IT with TS combination. A shorter production time was obtained on the walls with NIAC and higher IT-TS. No marked microstructural differences were observed comparing the walls, regardless of the cooling approach. However, microstructure tempering (hardness reduction) was observed in the walls deposited with NC using higher IT levels. [ABSTRACT FROM AUTHOR]

The proliferation of Industry 4.0 (I4.0) technologies has created a new manufacturing landscape for manufacturing, requiring that companies follow I4.0 trends to stay competitive. However, in this novel digital automated environment, these companies must also ensure that lean manufacturing principles are upheld. This study proposes a data-driven framework for analysing raw data across machines in manufacturing systems that can provide a comprehensive understanding of idle time and facilitate adjustments to reduce defect rates. This framework offers an alternative approach to improving manufacturing processes that involves utilising the power of I4.0 technologies in conjunction with lean manufacturing principles. This study's examination of unprocessed data also provides guidance on improving legislation. The findings of this study provide direction for future research in the field of manufacturing and offer useful advice to businesses wishing to integrate I4.0 technologies into their operations. [ABSTRACT FROM AUTHOR]

The blocking flow-shop scheduling problem, which is an NP-hard problem, has wide applications in industry. Many studies have focused primarily on single-objective optimization, such as minimizing the makespan or total flow time, which is insufficient for practical problems. In this study, a blocking flow-shop scheduling problem with bicriteria of the makespan and machine utilization is considered. A simple constructive heuristic, NEHCG, is proposed by developing new priority and tie-breaking rules based on the Nawaz–Enscore–Ham heuristic. In the new priority rule, the quartile deviation of job processing times is included for the first time, and the new tie-breaking rule is designed to break ties effectively in the insertion phase. Then, an improved constructive heuristic, PW_NEHCG, is presented by effectively combining NEHCG with an improved profile-fitting approach. Computational experiments show that the proposed constructive heuristics exhibit excellent performance compared to other well-known heuristics. [ABSTRACT FROM AUTHOR]

Gate allocation has always been a fundamental but critical issue in the daily operation of airports, which is related to service quality and schedule efficiency. In order to obtain reasonable and efficient gate allocation results, in this paper, a multi-commodity network flow model is proposed to describe the gate allocation process in flight flow, based on which a multi-objective optimization model is constructed. It not only comprehensively considers the flight information of aircraft arrivals and departures, but also integrates the broader interests of passengers, airlines, and airports. To solve it, a linear weighting technique is applied. In addition, K-means cluster analysis is used to explore different weight combinations, and on this basis, the idle time of the gate is introduced as a performance evaluation index to guide the selection of the final weight. By analyzing the optimization results of actual operation data, the proposed model significantly balances the interests of multiple parties and the number of flights at each gate and has a relatively high gate-utilization rate. It can provide rich decision support and a reasonable allocation scheme for airport management to a certain extent. [ABSTRACT FROM AUTHOR]

The classical economic growing quantity (EGQ) model is a key concept in the inventory control problems research literature. The EGQ model is commonly employed for the purpose of inventory control in the management of growing items, such as fish and farm animals, within industries such as livestock, seafood, and aviculture. The economic order quantity (EOQ) model assumes that customer demand is satisfied without interruption in each cycle; however, this assumption is not always true for some companies as they do not have continuous operations, except for item storage, during non-working times such as weekends, natural idle periods, or spare time. In this study, we extend the traditional EGQ model by incorporating the concept of working and non-working periods, resulting in the development of a new model called discontinuous economic growing quantity (DEGQ). Unlike the conventional EGQ model, the DEGQ model considers the presence of intermittent operational periods, in which the firm is actively engaged in its activities, and non-working periods, during which only storage-related operations occur. By incorporating this discontinuity, the DEGQ model provides a more accurate representation of real-world scenarios where businesses operate in a non-continuous manner, thus enhancing the effectiveness of inventory control and management strategies. The study aims to obtain the optimal number of periods in each cycle and the optimal slaughter age for the breeding items, and, subsequently, to find the optimal order size to minimize the total cost. Finally, we propose an optimal analytical procedure to determine the optimal solutions. This procedure entails finding the optimal number of periods using a closed-form equation and determining the optimal slaughter age by exhaustively searching the entire range of possible growth times.

This paper deals with sequencing problems for 'n' jobs on two machines, 'n' jobs on three machines and 'n' jobs on m machines. We have solved the sequencing problem by converting the processing time which is given in terms of trapezoidal fuzzy numbers into intervals using α-cut. An algorithm is provided for obtaining an optimal sequence and also for determining the minimum total elapsed time and idle time for each machine. To illustrate this, numerical examples are provided. [ABSTRACT FROM AUTHOR]

Abstract. The article studied the effect of transport vehicles on the grain harvester idle time during wheat, barley and rapeseed harvesting in 6 agricultural farms. In each of the farms one grain harvester and the established harvesting organization were studied without changing the unloading mode and the specific activities performed by the harvester operators and transportation vehicles. By multifactor regression analysis the effect of time for moving the transport vehicle on the grain harvester idle time was established. In addition, the value of the determination coefficient R2=0.54 reveals that 54% of the harvester idle time for unloading the grain hopper (Т1) change is due to the change of significant times and 46% to the effect of unmanageable factors. It has been established that the change in the time from opening the unloading auger to its activation depends on the position of transport vehicles on the field (t1) and the time for their movement to the harvester auger (t2). The results obtained can be used to minimize costs in the technological process of crop harvesting.

The proliferation of Industry 4.0 (I4.0) technologies has created a new manufacturing landscape for manufacturing, requiring that companies follow I4.0 trends to stay competitive. However, in this novel digital automated environment, these companies must also ensure that lean manufacturing principles are upheld. This study proposes a data-driven framework for analysing raw data across machines in manufacturing systems that can provide a comprehensive understanding of idle time and facilitate adjustments to reduce defect rates. This framework offers an alternative approach to improving manufacturing processes that involves utilising the power of I4.0 technologies in conjunction with lean manufacturing principles. This study’s examination of unprocessed data also provides guidance on improving legislation. The findings of this study provide direction for future research in the field of manufacturing and offer useful advice to businesses wishing to integrate I4.0 technologies into their operations.

Consider a region that requires to be protected from unauthorized penetrations. The border of the region, modeled as a unit line segment, consists of high priority segments that require the highest level of protection separated by low priority segments that require to be visited infinitely often. We study the problem of patrolling the border with a set of k robots. The goal is to obtain strategies that minimize the maximum idle time (the time that a point is left unattended) of each point of the high priority segments while visiting each point of the low priority segments infinitely often. We use the concept of single lid cover (segments of fixed length) where each high priority point is covered with at least one lid, and then we extend it to strong double-lid cover where each high priority point is covered with at least two lids, and the unit line segment is fully covered. Let λ k − 1 be the minimum lid length that accepts a single λ k − 1 -lid cover with k − 1 lids and Λ 2 k be the minimum lid length that accepts a strong double Λ 2 k -lid cover with 2 k lids. We show that 2 min ⁡ (Λ 2 k , λ k − 1) is the lower bound of the idle time when the max speed of the robots is one. To compute Λ 2 k and λ k − 1 , we present an algorithm with time complexity O (max ⁡ (k , n) log ⁡ n) where n is the number of high priority segments. Our algorithm improves by a factor of min ⁡ (n , k) the previous O (k n log ⁡ n) running time algorithm. For the upper bound, first we present a strategy with idle time λ k − 1 where robot k patrols the unit line segment, and robot i patrols the i -lid of a single λ k − 1 -lid cover with k − 1 lids. Then, we present a simple strategy with idle time 3 Λ 2 k that splits the unit line into not-disjoint k segments of equal length that robots synchronously cover, i.e., reaching the leftmost and rightmost point simultaneously. Then, we present a complex strategy that splits the unit line into k non-disjoint segments that robots asynchronously cover. We show that the combination of strategies one and two attains an approximation of 1.5 the optimal idle time and combining strategies one and third attains an optimal idle time. [ABSTRACT FROM AUTHOR]

This project is a case study conducted in a manufacturing company aiming at improving its productivity using line balancing techniques. Waste reduction, especially the time waste, is an important factor to shrink the manufacturing cost. The main purpose of this project is to suggest a better line balancing approach with an aim of reducing the idle time, work station number, and manpower requirement while improving the efficiency to meet the target production in the apparel manufacturing organization. For accomplishing the purpose, different line balancing methods named Largest Candidate Rule, Kilbridge & Wester method, and Ranked Positional Weight method carried out for analyzing the line efficiency, production rate, work station number, manpower requirement, and time utilization. Finally, an efficient and balanced line were proposed with respect to the auspicious outcome of the production area. Also, by using the line balancing techniques, a new sequence of work has been developed to arrange the work elements into the workstation. Some optimum layout has been proposed that has minimized the idle time and manpower requirement.

Most of the offline businesses do not run continuously for the entire day, therefore, the concept of idle time is inevitable. Natural idle time is referred to as the closing time when no demand is being fulfilled by the seller, the unproductive time when labor is not getting utilized but could be. In view of this, this paper investigates replenishment policies for the retailer who runs his business for only a part of a day and closes his shop for the remaining time. The demand gets fulfilled only during the opening time period while no customer is entertained during the closing part of the day. The retailer also faces issues of imperfect quality items in the lot received from his supplier. Thus, he carries out a rigorous inspection process of the entire lot so as to fulfill the demand with perfect quality items only. Under the above-stated circumstances, it is difficult to avoid shortages in the model. Thus, the model assumes fully backlogged shortages and is solved under a profit maximizing framework. The model is exemplified to understand its behavior. Further, to gain some managerial insights and to check the robustness of the model parameters, detailed sensitivity analysis is performed.

Uncertain queueing system is a waiting line in which the interarrival times and service times are both modeled by uncertain variables. This paper investigates four important performance characteristics of uncertain queueing system, including waiting time, idle time, total idle time and total busy time. The analytical formulas of uncertainty distributions of those performance characteristics are also derived separately. [ABSTRACT FROM AUTHOR]

Companies are looking for effective strategies to improve warehouse performance quality due to customers dissatisfaction of service. The order picking process is one of the main warehouse management strategies. As the inventory of stored items and the number of orders increased, the picking process and response time became more important. Effective coordination between order batching and order picking process is essential to improve the effeciency of the warehouse management system. In this paper, a novel Mixed- Integer Nonlinear Programming (MINLP) model for on-line order batching is proposed for improving the warehouse performance, which in turn results in the reduction of the response and idle times. The proposed method takes aim at the investigation of order classification for the first time in the picker-to-part system as a manual picking system and an online order batching system, with the intent of minimizing the turnover time and idle time. Besides, an order batching model in a blocked warehouse using a zoning system is proposed which is called Online Order Batching in Blocked Warehouse with One Picker for each Block (OOBBWOPB). The mentioned model is solved by two algorithms: Artificial Bee- Colony (ABC) algorithm and Ant-Colony (ACO) algorithm. Two numerical case studies are defined and analyzed using MATLAB software. According to the results compared with the results of Zhang et al. (2017) the proposed model shows better performance and the average customer order response time is significantly reduced (2017) and the ACO yields better results than ABC. [ABSTRACT FROM AUTHOR]

This research aimed to compare the rumination time estimated by an electronic monitoring system with direct visual observations of the rumination of dairy cows in a grazing-based system. Also, it aimed to estimate the agreement between different time intervals of the direct visual observations. To that end, we have observed twelve lactating cows for 16 h a day for 11 days. Then, we compared the data provided by the HealthyCow24® software with the visual observations to use as reference. After that, we estimated the Pearson’s correlation coefficients, the linear regression, and the Bland–Altman plot by using the SAS software. Results showed that the rumination data estimated by the HealthyCow24® software and the visual observations were highly correlated (0.81; P < 0.0001). In the Bland–Altman analysis, we observed that the average of the standard deviations between the visual observation and the electronic monitoring system was − 2.14 min during a 2-h period. The upper limit (95%) was 30.61 min/2 h and the lower limit (95%) was − 34.88 min/2 h. Moreover, visual observations at intervals of up to 15 min were correlated with the data estimated by the electronic monitoring system and observed at 5-min intervals. In conclusion, the Allflex SCR electronic monitoring system is efficient in measuring the rumination time of grazing cows. Also, direct visual observations with intervals no longer than 15 min are reliable when used for evaluating the behavior of cows without losing data accuracy. [ABSTRACT FROM AUTHOR]

Flow shop scheduling problem has a wide application in the manufacturing and has attracted much attention in academic fields. From other point, on time delivery of products and services is a major necessity of companies’ todays; early and tardy delivery times will result additional cost such as holding or penalty costs. In this paper, just-in-time (JIT) flow shop scheduling problem with preemption and machine idle time assumptions is considered in which objective function is minimizing the sum of weighted earliness and tardiness. A new non-linear mathematical model is formulated for this problem and due to high complexity of the problem meta-heuristic approaches have been applied to solve the problem for finding optimal solution. The parameters of algorithms are set by Taguchi method. Each parameter is tested in three levels. By implementation of many problems with different sizes these levels are determined .The proposed model is solved by three meta-heuristic algorithms: genetic algorithm (GA), imperialist competitive algorithm (ICA) and hybrid of GA and ICA. To evaluate the performance of the proposed algorithms many test problems have been designed. The Computational results indicate the superiority of the performance of hybrid approach than GA and ICA in finding thebest solution in reasonable computational time.

The study addresses the influence of milking duration of individual cows on the performance of conveyor-like rotary milking parlors and seeks to optimize their operation parameters and operating modes. The observational experiment was conducted in the Zhdanovsky Farm in Nizhny Novgorod Region, Russia. The dairy farm had a herd of 600 cows, divided into 10 groups by physiological characters and milk yield, and operated a 36 point milking parlor. Distribution of milking time of individual cows was studied using statistical analysis methods. The cyclogram of parlor operation and the functional connection of main parameters were analyzed using Maple analytical computing system, including its standard libraries and functions. The trends in idle time, which occurs due to undermilking of animals in one turn of the parlor, were studied. The idle time can result in overestimation of the number of stalls or decrease in the nameplate performance of the milking parlor by 30–40% from 120 to 93 cows per hour. Mathematical models, taking into account the influence of the milking time of individual animals (2 to 17 minutes) on the parameters of parlor operation, were developed. The algorithms of adaptive control over the rotational speed were proposed to minimize idle time in parlor operation and maintain the nameplate performance. The mathematical models, control algorithms and developed software can serves as a scientific basis for new designs of high-performance rotary milking parlors.

Gate allocation has always been a fundamental but critical issue in the daily operation of airports, which is related to service quality and schedule efficiency. In order to obtain reasonable and efficient gate allocation results, in this paper, a multi-commodity network flow model is proposed to describe the gate allocation process in flight flow, based on which a multi-objective optimization model is constructed. It not only comprehensively considers the flight information of aircraft arrivals and departures, but also integrates the broader interests of passengers, airlines, and airports. To solve it, a linear weighting technique is applied. In addition, K-means cluster analysis is used to explore different weight combinations, and on this basis, the idle time of the gate is introduced as a performance evaluation index to guide the selection of the final weight. By analyzing the optimization results of actual operation data, the proposed model significantly balances the interests of multiple parties and the number of flights at each gate and has a relatively high gate-utilization rate. It can provide rich decision support and a reasonable allocation scheme for airport management to a certain extent.