Mena, Rodrigo

Efficiency in supply chains is critically affected by the performance of operations within warehouses. For this reason, the activities related to the disposition and management of inventories are crucial. This work addresses the multi-level storage locations assignment problem for SKU pallets, considering divisible locations in the first level to improve the picking operation and reduce the travel times associated with the routes of the cranes. A mathematical programming model is developed considering the objective of minimizing the total travel distance, and in the background, maximizing the use of storage capacity. To solve this complex problem, we consider its decomposition into four subproblems, which are solved sequentially. To evaluate the performance of the model, two analysis scenarios based on different storage strategies are proposed to evaluate both the entry and exit distance of pallets, as well as the cost associated with the movements.

Wastewater treatment plants (WWTPs) face two fundamental challenges: on the one hand, they must ensure an efficient application of preventive maintenance plans for their survival under competitive environments; and on the other hand, they must simultaneously comply with the requirements of reliability, maintainability, and safety of their operations, ensuring environmental care and the quality of their effluents for human consumption. In this sense, this article seeks to propose a cost-efficient alternative for the execution of preventive maintenance (PM) plans through the formulation and optimization of the opportunistic grouping strategy with time-window tolerances and non-negligible execution times. The proposed framework is applied to a PM plan for critical high-risk activities, addressing primary treatment and anaerobic sludge treatment process in a wastewater treatment plant. Results show a 26% system inefficiency reduction versus the initial maintenance plan, demonstrating the capacity of the framework to increase the availability of the assets and reduce maintenance interruptions of the WWTP under analysis.

Wastewater treatment is a critical and necessary task every human settlement is obligated to address. If not, the consequences might be catastrophic, not just for humans but for the ecosystems as well, pushing research into finding new ways to improve wastewater treatment processes to make them safer and more efficient. Hence, there is a need to address matters, such as reliability and maintainability of Wastewater Treatment Plants (WWTP), when analyzing the availability and operational conditions. These should be addressed by analyzing the plant operational effectiveness impact (P-OEI), and in this article specifically, a WWTP study case to identify design flaws or improvement opportunities. A vital aspect of a complex system is to determine the contribution to resilience, reliability, and availability of every element embedded in the system. This is performed by adapting and applying the P-OEI methodology and real data of a WWTP located in Chile. This methodology breaks down the system into several levels of disaggregation similar to RBD methodology, analyzing the upstream for availability and the downstream for the P-OEI analysis from the system itself to the individual elements within subsystems. The potential impact on the overall system’s lack of efficiency is also quantified by an Expected Operational Impact (EOI) index, which is also calculated by the methodology. The P-OEI and EOI analyses performed in this study are powerful tools to assess the design and performance of complex systems and WWTP in particular.