Optical film cutting is a critical upstream process in LCD and electronics manufacturing, characterized by high material costs, diverse order specifications, and frequent demand fluctuations that complicate production planning. In practice, manufacturers must coordinate cutting methods, manage semi-finished inventory across multiple periods, and handle recyclable waste simultaneously. However, these decisions are often made independently, resulting in excessive material usage, unstable inventory levels, and avoidable waste. This study develops a multi-period optimization framework for LCD optical film cutting that integrates two production routes, namely slitting and miter cutting, with inventory control and waste recycling. The model captures key operational trade-offs, including process selection, timing of intermediate production, and recycling decisions. It first minimizes total costs, incorporating material, processing, inventory, and waste-related costs, and is further extended into a bi-objective formulation that jointly considers operational cost and waste generation. The primary contribution of this research is to provide an integrated decision framework that reflects real production conditions in electronics manufacturing. By linking cutting, inventory, and recycling decisions across multiple periods, the model enables more coordinated planning and improved resource utilization. A case study with large-scale order data shows that the proposed approach can reduce waste, stabilize inventory, and improve the balance between cost efficiency and environmental performance. The analysis also reveals that cutting assignments tend to concentrate around several preferred angle configurations under realistic production conditions, suggesting the existence of practical process preferences and recurring operational patterns in optical film manufacturing. Overall, this study offers a practical planning tool for optical film converting operations and is applicable to other high-value, roll-based materials in precision manufacturing environments where inventory linkage, process flexibility, and recyclable waste are critical considerations.

Issues of industrial waste recycling are very relevant for the entire global scientific community. The search for technological solutions that would allow the production of high-quality materials using industrial waste will not only reduce the environmental load, but also expand the raw material base for the production of gypsum materials. The study examined the possibility of improving the surface quality of molded gypsum samples by replacing the metal mold with a plastic one and introducing a surfactant into the raw mixture. As a result of the research, it was found that the use of a surfactant and a plastic mold allows to avoid defects on the surface of the samples. At the same time, the use of a plastic mold, which has low adhesion to the citrogypsum-based binder, helps to reduce the amount of adhesion friction and optimize the raw mixture compaction process. This makes it possible to obtain samples with improved physical and mechanical characteristics (compressive strength increases by 30–85.5%, average density - by 1.7–2.7% and water absorption decreased by 1.7–16%) or lower consumption of binder up to 20% compared to samples prepared in metal mold.

For decades, due to the increasing generation of waste and its negative environmental impacts, efficient municipal solid waste management (MSWM) has become a major concern of sustainable development. On the other hand, selecting an appropriate strategy remains a critical issue for municipal authorities without applying a multi-criteria decision-making (MCDM) approach. This study aims to select the best MSWM strategy from five potential MSW management strategies under various factors that influence waste strategy selection, such as economic, social, technical, and environmental factors. This study used three fuzzy integrated MCDM methods, namely the Decision-Making Trail and Evaluation Laboratory (DMATEL), the Analytic Network Process (ANP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to select best MSWM strategies. The study used data from a survey of experts who had knowledge of waste management. The survey data was then analyzed using the DMATEL, ANP and TOPSIS methods under a fuzzy environment. The Fuzzy DEMATEL method is used to identify the causal relationships among the criteria and sub-criteria, while ANP is applied to determine the relative weights of MSWM strategy selection sub-criterion. Finally, TOPSIS is used to rank the waste management strategies depending on established sub-criteria. The result of fuzzy TOPSIS demonstrated that recycling of municipal solid waste is the best alternative which has the highest closeness coefficient followed by reuse. Thus, the result of this study revealed that MSWM strategies are ranked as: waste recycling (A1), reuse (A2), reduce (A1), energy recovery (A4), and disposal (A5), with closeness coefficient values of 0.80, 0.61, 0.60, 0.47, and 0.17, respectively.