An improved co-evolutionary algorithm for green manufacturing by integration of recovery option selection and disassembly planning for end-of-life products

There is a strong need for recovery decision-making for end-of-life (EOL) products to satisfy sustainable manufacturing requirements. This paper develops and tests a profit maximisation model by simultaneously integrating recovery option selection and disassembly planning. The proposed model considers the quality of EOL components. This paper utilises an integrated method of multi-target reverse recursion and partial topological sorting to generate a feasible EOL solution that also reduces the complexity of genetic constraints handling. In order to determine recovery options, disassembly level and disassembly sequence simultaneously, this paper develops an improved co-evolutionary algorithm (ICA) to search for an optimal EOL solution. The proposed algorithm adopts the evolutionary mechanism of localised interaction and endosymbiotic competition. Further, an advanced local search operator is introduced to improve convergence performance, and a global disturbance strategy is also suggested to prevent premature convergence. Finally, this paper conducts a series of computational experiments under various scenarios to validate the meta-heuristic integrated decision-making model proposed and the superiority of the developed ICA. The results show that the proposed approach offers a strong and flexible decision support tool for intelligent recovery management in a ubiquitous information environment. We discuss the theoretical and practical contributions of this paper and implications for future research.     

Environmental impact assessment and the planning process of major sports events in Brazil: a case study of the Rio 2007 Pan American Games

This paper investigates the implementation and enforcement of environmental licensing and environmental impact assessment (EIA) regulations and decisions in the context of the Rio 2007 Pan American Games in Brazil. The methodology includes detailed case study analysis involving document analysis and interviews with key stakeholders. The results demonstrate that implementation and enforcement of EIA and environmental licensing still have a long way to go in terms of being fully effective in Brazil. Despite this, in the scope of the case study, the results showed that implementation and enforcement of environmental licensing and EIA regulations and decisions seem to be undertaken according to relevant regulations in the context of the Pan American Village. Finally, recommendations for major sports events and for the Brazilian context to strengthen its regulatory framework for environmental licensing and EIA are developed.     

More MILP models for integrated process planning and scheduling

The integration of process planning and scheduling is important for an efficient utilisation of manufacturing resources. In general, there are two types of models for this problem. Although some MILP models have been reported, most existing models belong to the first type and they cannot realise a true integration of process planning and scheduling. Especially, they are completely powerless to deal with the cases where jobs are expressed by network graphs because generating all the process plans from a network graph is difficult and inefficient. The network graph-specific models belong to the other type, and they have seldom been deliberated on. In this research, some novel MILP models for integrated process planning and scheduling in a job shop flexible manufacturing system are developed. By introducing some network graph-oriented constraints to accommodate different operation permutations, the proposed models are able to express and utilise flexibilities contained in network graphs, and hence have the power to solve network graph-based instances. The established models have been tested on typical test bed instances to verify their correctness. Computational results show that this research achieves the anticipant purpose: the proposed models are capable of solving network graph-based instances.     

Capacity-filtering algorithms for finite-capacity planning of a flexible flow line

This paper addresses finite-capacity planning (or medium-term scheduling) issues in a flexible flow line such as a semiconductor fabrication (Fab), liquid crystal display (LCD) Fab, or printed circuit board (PCB) Fab. In such a flexible flow line, medium-term schedules such as release schedules and output schedules are critical to achieving the goal of full-capacity and on-time production. However, existing finite-capacity planning methods do not adequately reflect the actual capacity profiles of the Fab. This paper presents capacity-filtering algorithms for generating a finite-capacity loading-profile from an infinite-capacity loading-profile at a processing stage in a Fab. In addition, two types of finite-capacity planning problems are described, and ways to use the algorithms in solving these problems presented. Performance analyses using a real-life case study show that the proposed method is superior to existing methods. It is postulated that the results presented can be used as a building block for obtaining medium-term schedules for the entire Fab.     

A framework for ICT-enabled real-time production planning and control

This paper aims to develop a conceptual framework for real-time production planning and control(PPC).Firstly,we discuss the most prominently applied contemporary information and communication technologies for PPC.Enterprise resource planning(ERP) systems that integrate the value chain in an enterprise,manufacturing execution systems that manage and control the production on shopfloor,and advanced planning and scheduling(APS)systems that develop solutions for complex planning problems are the planning and control systems that have been analyzed.We emphasize the application of radio frequency identification as the most advanced and promising emerging real-time data capture technology that is currently available to manufacturers.Having analyzed the features and shortcomings of the individual systems perse,and by considering the advantages that may be realized through effective integration of these otherwise discrete systems,we propose a framework for real-time PPC.     

A new heuristic for integrated process planning and scheduling in reconfigurable manufacturing systems

Integrated process planning and scheduling (IPPS) is a manufacturing strategy that considers process planning and scheduling as an integrated function rather than two separated functions performed sequentially. In this paper, we propose a new heuristic to IPPS problem for reconfigurable manufacturing systems (RMS). An RMS consists mainly of reconfigurable machine tools (RMTs), each with multiple configurations, and can perform different operations with different capacities. The proposed heuristic takes into account the multi-configuration nature of machines to integrate both process planning and scheduling. To illustrate the applicability and the efficiency of the proposed heuristic, a numerical example is presented where the heuristic is compared to a classical sequential process planning and scheduling strategy using a discrete-event simulation framework. The results show an advantage of the proposed heuristic over the sequential process planning and scheduling strategy.     

Impact assessment: tiering approaches for sustainable development planning and decision-making of a large infrastructure project

ABSTRACT

The objective of this paper is to analyze a tiering scoping approach developed to identify critical multidimensional sustainability issues and impacts of a large infrastructure project: the land transport project linking northern Brazil with a new port on Guyana’s coast. The Inter-American Development Bank awarded a technical assignment to develop the terms of reference of a country environmental assessment, a strategic environmental and social assessment and an environmental and social impact assessment of the project(s). The complexity of the issues at stake lead to the design of a tiered assessment process supported by wide-ranging participative sessions involving 170 individuals from Guyana and Brazil and from diverse sectors. The process identified ex ante conditionalities, critical factors for decision-making and valued socioenvironmental and governance components. Such complex and determinant planning initiatives for the future of a country need to be supported by comprehensive, well-sequenced scoping processes.     

An evaluation framework for product planning using FANP,QFD and multi-choice goal programming

Technological innovation and satisfaction of customer needs are the keys to survival and success for firms, especially in global competitive high-tech industries. Since new products are usually a source of new sales and profits, the success of new product development (NPD) is essential to maintain a competitive edge and to make a decent profit in a longer term. Therefore, how to develop products that deliver the quality and functionality customers demand while generating the desired profits becomes an important task for the manufacturers. In this paper, a framework with two phases is constructed for facilitating the selection of engineering characteristics (ECs) for product design. In the first phase, quality function deployment (QFD) is incorporated with the supermatrix approach of analytic network process (ANP) and the fuzzy set theory to calculate the priorities of ECs with the consideration of the interrelationship among factors and the impreciseness and vagueness in human judgments and information. In the second phase, multi-choice goal programming model is constructed by considering the outcome from the first phase and other additional goals, such as NPD cost and manufacturability, in the attempt to select the most suitable ECs. A case study of the product design process of backlight unit (BLU) in thin film transistor liquid crystal display (TFT-LCD) industry in Taiwan is carried out to verify the practicality of the proposed framework.     

Flexible servo riveting system control strategy based on the RBF network and self-pierce riveting process

As more and more composite materials are used in lightweight vehicle white bodies, self-pierce riveting (SPR) technology has attracted great attention. However, the existing riveting tools still have the disadvantages of low efficiency and flexibility. To improve these disadvantages and the riveting qualification rate, this paper improves the control scheme of the existing riveting tools, and proposes a novel controller design approach of the flexible servo riveting system based on the RBF network and SPR process. Firstly, this paper briefly introduces the working principle and SPR procedure of the servo riveting tool. Then a moving component force analysis is performed, which lays the foundation for the motion control. Secondly, the riveting quality inspection rules of traditional riveting tools are used for reference to plan the force-displacement curve autonomously. To control this process, the riveting force is fed back into the closed-loop control of the riveting tool and the riveting speed is computed based on the admittance control algorithm. Then, this paper adopts the permanent magnet synchronous motor (PMSM) as the power of riveting tool, and proposes an integral sliding mode control approach based on the improved reaching law and the radial basis function (RBF) network friction compensation for the PMSM speed control. Finally, the proposed control approach is simulated by Matlab, and is applied to the servo riveting system designed by our laboratory. The simulation and riveting results show the feasibility of the designed controller. The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-022-00403-3