Abstract
The global economic crisis makes it necessary to increase business competitiveness. Lean is a manufacturing philosophy that deserves the attention of employers and their employees, since its objectives are to increase productivity, reduce waste, and optimize available resources. The 5S method is a lean tool that can improve productivity by improving the organization of the workplace. A brief survey of the market showed that there are several organizations dedicated to training and sharing this type of knowledge but only a few of them have digital tools available. Therefore, the use of a digital serious game that helps to understand the 5S method can effectively support an alternative form of learning. This article proposes a serious game that aims to respond to this need. This practical approach encourages the player to learn by trial and error. Information displayed throughout the game enhances learning, without a cognitive overload for the player. The game's evaluation has shown that our approach is efficient and results in the learning of 5S concepts. © 2013 IEEE.

Abstract
In this paper we present a hybrid exact-heuristic method to improve a branch-and-price algorithm to solve the unrelated parallel machines with sequence-dependent setup times scheduling problem. As most of the computational time in the column generation (CG) process is spent in subproblems, two new heuristics to solve the subproblems are embedded in the branch-and-price (BP) framework with the aim to improve the efficiency of the process in obtaining optimal solutions. Computational results show that the proposed method improves a state-of-the-art BP algorithm from the literature, providing optimal solutions for large instances (e. g. 50 machines and 180 jobs) of the parallel machine scheduling problem with sequence dependent setup times, in significantly less time. One of the proposed approaches reduces, in average, to a half the time spent in the root of the branch-and-price tree and to a quarter the time spent in the full branch-and-price algorithm.

Abstract
This paper studies a real world dedicated parallel machine scheduling problem with sequence dependent setups, different machine release dates and additional resources (PMSR). To solve this problem, two previously proposed models have been adapted and a novel objective function, the minimisation of the sum of the machine completion times, is proposed to reflect the real conditions of the manufacturing environment that motivates this work. One model follows the strip-packing approach and the other is time-indexed. The solutions obtained show that the new objective function provides a compact production schedule that allows the simultaneous minimisation of machine idle times and setup times. In conclusion, this study provides valuable insights into the effectiveness of different models for solving PMSR problems in real-world contexts and gives directions for future research in this area using complementary approaches such as matheuristics. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.