The processing time of the machine is assumed fixed in several studies. In many real industrial applications, the processing time is affected by learning and forgetting effects. This research proposes a scheduling approach to support a manufacturing system under learning/forgetting effect. The approach is supported by a Multi-Agent System to perform the scheduling activities in a quasi-real-time and in general manufacturing systems. A simulation environment is developed to test the proposed approach and the results are compared with a benchmark model for evaluating several performance measures of the manufacturing system. The simulation results highlight how the proposed approach improves all the performance measures under different conditions of inter-arrival time, learning and forgetting rates. A complete Analysis of the Variance highlights the main effects on the performance measures to support the decision maker of the manufacturing system.

This study examines the robust relationships between Roblox's business model, collaborative learning, participation in the decision-making process, and cooperative literacy within the Indonesian Roblox community. All hypotheses were substantiated, emphasizing the significance of understanding the business model, promoting collaborative learning, and encouraging active involvement in decision-making activities for fostering cooperative literacy among players. The research employed an exploratory research design with a quantitative approach. Sampling bias and self-reported data are acknowledged limitations, along with the cross-sectional design's inability to establish causality. To address these constraints, future research should employ longitudinal methods, diverse data collection approaches, and intervention studies. Cross-cultural research comparing the Indonesian Roblox community with other cultural contexts is also encouraged. Practical recommendations include integrating features that support collaborative learning and decision-making participation within the Roblox platform. Collaboration between educational institutions and Roblox to use the platform as an educational tool is suggested, offering students a unique opportunity to develop cooperative literacy skills. These findings offer valuable insights into cooperative literacy and community engagement within the Roblox ecosystem, providing a roadmap for its development. This research contributes to the platform's growth and success in Indonesia, making it a more cooperative and informed community.

This study aims to investigate the multi-item inventory model in a production/rework system with multiple production setups. Rework can be depicted as the transformation of production rejects, failed, or non-conforming items into re-usable products of the same or lower quality during or after inspection. Rework is very valuable and profitable, especially if materials are limited in availability and also pricey. Moreover, rework can be a good contribution to a ‘green image environment’. In this paper, we establish a multi-item inventory model to determine the optimal inventory replenishment policy for the economic production quantity (EPQ) model for imperfect, deteriorating items with multiple productions and rework under inflation and learning environment. In inventory modelling, Inflation plays a very important role. In one cycle, production system produces items in n production setups and one rework setup, i.e. system follows (n, 1) policy. To reduce the deterioration of products preservation technology investment is also considered in this model. Holding cost is taken as time dependent. We develop expressions for the average profit per time unit, including procurement of input materials, costs for production, rework, deterioration cost and storage of serviceable and reworkable lots. Using those expressions, the proposed model is demonstrated numerically and the sensitivity analysis is also performed to study the behaviour of the model.

Creating and maintaining a learning organization is a competitive advantage, which would be the result of valuable outcomes such as innovation, efficiency and the better convergence with environment. In addition, learning is the best way to preserve life, survival and growth of organizations in future. In this regard, this study examined the relationship between trust and learning organizations. This study had one main hypothesis and five sub-hypotheses. Research method was descriptive, and t-test and correlation tests were used to determine the relationships between variables. The statistical populations of this study were employees and faculty members of Payam Noor University in east Azerbaijan province, Iran. The results of this study show that there was a meaningful and positive relationship between trust in organization and learning organizations. Therefore, it is recommended that organizations dismantle the barriers of trust, be promoted the trust-builder interactive relationships; be improved and be promoted the mechanisms of interpersonal communications. The firms also have to develop competencies, empower and promote the spirit of cooperation. On the other hand, organizations must prioritize the fostering and promoting the strategic and interactive thinking of staff.

This paper presents an empirical investigation on the effects of the computer games on some female students who attended the secondary schools in Iran over the period 2013-2014. The population of the survey includes 7542 female students who attend secondary schools in Babol County, Iran. The study selects 364 people as a sample and the sampling was accomplished based on random cluster way. The necessary data were collected using two questionnaires of computer games and decline of study with 25 questions in Likert 5 points and there were validated by experts and specialists in the field of educational technology and psychology. In addition, Cronbach alpha was calculated as 0.828, which was well above the minimum acceptable level. Using Pearson correlation test as well as one-way t-student, the study indicates that most female students of secondary school in Babol County used computer games. In our survey, there was a strong relationship between computer games with decline of study and study motivation, and there was a weak relationship between computer games and learning of girl students of secondary school in Babol County.

In this paper, we develop a two-warehouse imperfect production model under two cases: (i) model starts with shortages (ii) model ends with shortages. Most of the researchers proposed the models for perfect items but we develop for imperfect quality items, which is very realistic. Demand is taken as time dependent and dependent on the production. Holding cost in rented warehouse (RW) is greater than own warehouse (OW). Deterioration is taken as Weibull distribution in both OW and RW. Shortages are allowed and partially backlogged. The effect of learning on production cost is also considered. Learning from one cycle to other cycle, improve the efficiency of the organization. A numerical example including the sensitivity analysis is given to validate the results of the production-inventory model.

This paper presents a unified multi items general inventory model for integrated production of new items and remanufacturing of returned and defected items for a finite planning horizon. In this paper, a production model that takes into account learning, instantaneous deterioration rate and inflation is proposed. In addition, we also consider that the holding cost is a non-negative, non-decreasing and continuous function of time. In this model, the preservation technology is used to reduce the rate of product deterioration. A theory is developed to find the optimal solution of the proposed model; it is then exemplified with the help of several numerical examples. An efficient solution procedure is also provided to find the optimal strategy. Finally, sensitivity of the optimal solution to changes in the values of different parameters of the system and the convexities of the cost functions are also studied and represented through the graphs.

In this study, a volume flexible inventory system for deteriorating items with stock & time dependent demand has been developed over a finite planning horizon. Shortages are permitted with partial backorder. Uncertainties are inherent in real inventory problems due to complexities of market situation. This uncertainty can be handled by the concept of randomness. As a result, backorder rate is taken as random and follows a probability distribution. All the costs are influenced by the learning effect. The optimal number of production cycles that minimize the total cost is considered. Numerical illustrations together with sensitivity analysis are given to elucidate the model. Furthermore, the numerical results of the finite planning horizon model have been plotted graphically.

The classical production-inventory model assumes that both demand and set-up costs are constant. However, in real manufacturing environment, managers usually embark on continuous improvement programmes that often lead to more effective use of tools and machineries and consequently reduction in set-up costs. In fact, constant emphasis on reduction of set-up costs is usually cited as one of the factors responsible for the efficiency of Japanese manufacturing methods. On the other hand, the demand for seasonal product is often characterized by a mixture of time-dependent patterns over the entire season. This paper investigates the effect of learning-based reduction in set-up costs on the optimal schedules and costs of a production-inventory system for deteriorating seasonal products. The demand pattern is a general three-phase ramp-type demand function that represents the various phases of demand commonly observed in many seasonal products in the market. A two-parameter Weibull-distribution function is used for the deterioration of items in order to make the model more generalized and realistic. The study further presents two different multi-period production strategies that can ensure a fast-response to customers’ demand and compare them with the usual single period strategy. The Numerical example and sensitivity analysis shows that learning-based reduction in set-up costs leads to higher production frequency and shorter production runs which are vital aspects of the just-in-time (JIT) philosophy.