Optimizing production scheduling of steel plate hot rolling for economic load dispatch under time-of-use electricity pricing

Time-of-Use (TOU) electricity pricing provides an opportunity for industrial users to cut electricity costs. Although many methods for Economic Load Dispatch (ELD) under TOU pricing in continuous industrial processing have been proposed, there are still difficulties in batch-type processing since power load units are not directly adjustable and nonlinearly depend on production planning and scheduling. In this paper, for hot rolling, a typical batch-type and energy intensive process in steel industry, a production scheduling optimization model for ELD is proposed under TOU pricing, in which the objective is to minimize electricity costs while considering penalties caused by jumps between adjacent slabs. A NSGA-II based multi-objective production scheduling algorithm is developed to obtain Pareto-optimal solutions, and then TOPSIS based multi-criteria decision-making is performed to recommend an optimal solution to facilitate filed operation. Experimental results and analyses show that the proposed method cuts electricity costs in production, especially in case of allowance for penalty score increase in a certain range. Further analyses show that the proposed method has effect on peak load regulation of power grid.Comment: 13 pages, 6 figures, 4 table

Stochastic make-to-stock inventory deployment problem: an endosymbiotic psychoclonal algorithm based approach

Integrated steel manufacturers (ISMs) have no specific product, they just produce finished product from the ore. This enhances the uncertainty prevailing in the ISM regarding the nature of the finished product and significant demand by customers. At present low cost mini-mills are giving firm competition to ISMs in terms of cost, and this has compelled the ISM industry to target customers who want exotic products and faster reliable deliveries. To meet this objective, ISMs are exploring the option of satisfying part of their demand by converting strategically placed products, this helps in increasing the variability of product produced by the ISM in a short lead time. In this paper the authors have proposed a new hybrid evolutionary algorithm named endosymbiotic-psychoclonal (ESPC) to decide what and how much to stock as a semi-product in inventory. In the proposed theory, the ability of previously proposed psychoclonal algorithms to exploit the search space has been increased by making antibodies and antigen more co-operative interacting species. The efficacy of the proposed algorithm has been tested on randomly generated datasets and the results compared with other evolutionary algorithms such as genetic algorithms (GA) and simulated annealing (SA). The comparison of ESPC with GA and SA proves the superiority of the proposed algorithm both in terms of quality of the solution obtained and convergence time required to reach the optimal/near optimal value of the solution

Three resilient megastructures by Pier Luigi Nervi

Resilience, as the ability of a structure to withstand threats and continue to function, it is normally related to durability and performance to accepted standards over time. The resilience of a structure can be threatened by poor design, changes in the public's perception of style, the potential for a change-in-use and structural attack; catastrophic events such as fire, explosion or impact are usually considered the main threats for Resilience. In the contemporary built environment Resilience is considered increasingly important; it has, in fact, become one of the major design issues, especially for large, iconic or public and prominent structures: this has not always been the case. Following the Second World War, building designers faced the necessity to conceive projects within severe financial constraints, hence the proliferation of a low quality and limited life-span structures; buildings which were designed to be replaceable, cheap and perhaps anonymous. This was thought to be an effec-tive answer to quickly accommodate the large number of people moving towards the urban environment partly destroyed by the WWII. These very buildings now constitute the backbone of our urban scenery and although some still function adequately, many are perfect examples of structures which exhibit a lack of re-silience. Fortunately, there were a few designers who refused this post-war tendency and attempted to design lasting structures of quality: most of them were engineers. This is not a coincidence, engineers had less to do with the issue of providing residential accommodations and more with the erection of large structures which necessitated a higher quality control on materials and technologies: Pier Luigi Nervi was one of them. This work considers three large structures designed and built fifty years ago,in 1961, by the Italian engineer. The structures are the Bus Station at the George Washington Bridge in New York (USA); The Burgo Paper Mill in Mantua (Italy); and the Palace of Labour in Turin (Italy). All of these buildings are hybrid structures (concrete and steel), an unusual choice for Nervi that perhaps reects the design climate at the time; These buildings reacted quite differently to the events that have occurred over the past half century. One of the key factors to achieve resilience it is considered to be the quality of the buildings, which includes their ability to perform maintenance. The lack of which for whatever reason, this paper aims to demonstrate, will inevitably result in a weak performance in terms of resilience on the long run

CSP: there is more than one way to model it.

In this paper, we present an approach for conceptual modelling of con- straint satisfaction problems (CSP). The main objective is to achieve a similarly high degree of modelling support for constraint problems as it is already available in other disciplines. The approach uses diagrams as operational basis for the development of CSP models. To facilitate a broader scope, the use of available mainstream modelling languages is adapted. In particular, the structural aspects of the problem are visually expressed in UML, complemented by a textual representation of rela- tions and constraints in OCL. A case study illustrates the expositions and deployment of the approach

Global method for a class of operation optimization problem in steel rolling systems

Many steel products are produced in hot or cold rolling lines with multiple stands. The steel material becomes thinner after being rolled at each stand. Steady-state parameters for controlling the rolling line need to be set so as to satisfy the final product specifications and minimize the total energy consumption. This paper develops a generalized geometric programming model for this setting problem and proposes a global method for solving it. The model can be expressed with a linear objective function and a set of constraints including nonconvex ones. Through constructing lower bounds of some components, the constraints can be converted to convex ones approximately. A sequential approximation method is proposed in a gradually reduced interval to improve accuracy and efficiency. However, the resulting convex programming model in each iteration is still complicated. To reduce the power, it is transformed into a second-order cone programming (SOCP) model and solved using alternating direction method of multipliers (ADMM). The effectiveness of the global method is tested using real data from a hot-rolling line with seven stands. The results demonstrate that the proposed global method solves the problem effectively and reduces the energy consumption

Computer-aided analysis and design of the shape rolling process for producing turbine engine airfoils

Mild steel (AISI 1018) was selected as model cold-rolling material and Ti-6Al-4V and INCONEL 718 were selected as typical hot-rolling and cold-rolling alloys, respectively. The flow stress and workability of these alloys were characterized and friction factor at the roll/workpiece interface was determined at their respective working conditions by conducting ring tests. Computer-aided mathematical models for predicting metal flow and stresses, and for simulating the shape-rolling process were developed. These models utilize the upper-bound and the slab methods of analysis, and are capable of predicting the lateral spread, roll-separating force, roll torque and local stresses, strains and strain rates. This computer-aided design (CAD) system is also capable of simulating the actual rolling process and thereby designing roll-pass schedule in rolling of an airfoil or similar shape. The predictions from the CAD system were verified with respect to cold rolling of mild steel plates. The system is being applied to cold and hot isothermal rolling of an airfoil shape, and will be verified with respect to laboratory experiments under controlled conditions

An Iterated Greedy Algorithm for a Parallel Machine Scheduling Problem with Re-entrant and Group Processing Features

This research paper addresses a novel parallel machine scheduling problem with re-entrant and group processing features, specifically motivated by the hot milling process in the modern steel manufacturing industry. The objective is to minimize the makespan. As no existing literature exists on this problem, the paper begins by analyzing the key characteristics of the problem. Subsequently, a mixed integer linear programming model is formulated. To tackle the problem, an improved iterated greedy algorithm (IGA) is proposed. The IGA incorporates a problem-specific heuristic to construct the initial solution. Additionally, it incorporates an effective destruction and reconstruction procedure. Furthermore, an acceptance rule is developed to prevent the IGA from getting stuck in local optima. The proposed approach is evaluated through computational experiments. The results demonstrate that the proposed IGA outperforms three state-of-the-art meta-heuristics, highlighting its high effectiveness. Overall, this research contributes to the understanding and solution of the parallel machine scheduling problem with re-entrant and group processing features in the context of the hot milling process. The proposed algorithm provides insights for practical applications in the steel manufacturing industry