Modelling and condition-based control of a flexible and hybrid disassembly system with manual and autonomous workstations using reinforcement learning

Remanufacturing includes disassembly and reassembly of used products to save natural resources and reduce emissions. While assembly is widely understood in the field of operations management, disassembly is a rather new problem in production planning and control. The latter faces the challenge of high uncertainty of type, quantity and quality conditions of returned products, leading to high volatility in remanufacturing production systems. Traditionally, disassembly is a manual labor-intensive production step that, thanks to advances in robotics and artificial intelligence, starts to be automated with autonomous workstations. Due to the diverging material flow, the application of production systems with loosely linked stations is particularly suitable and, owing to the risk of condition induced operational failures, the rise of hybrid disassembly systems that combine manual and autonomous workstations can be expected. In contrast to traditional workstations, autonomous workstations can expand their capabilities but suffer from unknown failure rates. For such adverse conditions a condition-based control for hybrid disassembly systems, based on reinforcement learning, alongside a comprehensive modeling approach is presented in this work. The method is applied to a real-world production system. By comparison with a heuristic control approach, the potential of the RL approach can be proven simulatively using two different test cases.

A Comprehensive Modeling of the Discrete and Dynamic Problem of Berth Allocation in Maritime Terminals

In this study, the discrete and dynamic problem of berth allocation in maritime terminals, is investigated. The suggested resolution method relies on a paradigm of optimization with two techniques: heuristic and multi-agent. Indeed, a set of techniques such as the protocol of negotiation named contract net, the multi-agent interactions, and Worst-Fit arrangement technique, are involved. The main objective of the study is to propose a solution for attributing m parallel machines to a set of activities. The contribution of the study is to provide a detailed modeling of the discrete and dynamic berth allocation problem by establishing the corresponding models using a multi-agent methodology. A set of numerical experiments are detailed to prove the performance of the introduced multi-agent strategy compared with genetic algorithm and tabu search.

Analysis of Expansion Joint - A Case Study

Automotive, Aerospace, Pipeline industries widely use Bellows. Different types of bellows are used in these industries. The bellows are used for contraction or expansion applications. Repeated variable pressure loading and displacement on Metallic bellows joints results in bellows failure. This paper is a comprehensive modeling and analysis of an axial type exhaust metallic bellow due to varying pressure load and circumferential and radial displacement. All analysis completed using ANSYS software considering variable pressure load and cylindrical displacement as a boundary condition and perused the consequences. Stress distribution in the conditions of Case (i) variable pressure load and Case (ii) displacement are obtained. Keywords: ANSYS, FE Bellows, Finite Element Analysis, Bellow Failures

Mitigating Well Construction Challenges of a Caspian Deepwater Exploratory Well: A Cementing Perspective

BP returned to Caspian deepwater exploratory drilling in 2019. The exploration well was drilled on the Shafag-Asiman structure in water depths greater than 2,000 ft. Well challenges included high shallow water flow (SWF) risk with multiple re-spuds on the nearest offset, lost circulation due to complex wellbore geometry combined with a narrow pore and fracture gradient window, and uncertainty in pore pressure prediction in abnormally pressured formations with a new depositional model. In addition, a well total depth more than 23,000 ft, eight string casing design and bottom-hole pressures greater than 20,000 psi presented a truly modern-day challenge to well integrity. A six-month planning phase for the cementing basis of design concluded by delivering slurry designs capable of combating SWF, qualified by variable-speed rotational gel strength measurement. Engineered lost circulation with selective placement of wellbore strengthening materials in combination with cement and mechanical barriers to provide isolation and integrity for the life of the well. Exhaustive pilot testing to account for changes required a cement design based on pore pressure variation and comprehensive modeling for hydraulics, centralizer placement, and mud displacement. This was complemented by a custom centralizer testing process specifically designed to simulate forces exerted in wells with similar complexity. Long-term effects on cement were evaluated, not only for placement but also for future operations including pressure and temperature cycles during wellbore construction or abandonment.