Simultaneous Production and Maintenance Planning for a Single Capacitated Resource facing both a Dynamic Demand and Intensive Wear and Tear

Abstract This paper presents a generic modeling framework to simultaneously decide about production quantities and maintenance operations for a capacitated resource facing a dynamic demand for different types of products. As the resource needs to be setup for each specific type of product, a lot-sizing problem occurs. In addition it is assumed that production causes intensive wear and tear. For this reason frequent maintenance activities need to be coordinated with the production operations in order to efficiently use the capacitated resource. A single generic model is presented to capture alternative forms of maintenance and different modes of interaction between maintenance and setups. As the model is numerically intractable for standard branch & bound algorithms, we solve it heuristically via a decomposition using a Fix-and-Optimize approach. Numerical results show that the proposed solution method produces high-quality results quickly. We further study the impact of simultaneous vs. sequential decisions about production and maintenance in the case of intensive wear and tear

The Application of Ant Colony Optimization

The application of advanced analytics in science and technology is rapidly expanding, and developing optimization technics is critical to this expansion. Instead of relying on dated procedures, researchers can reap greater rewards by utilizing cutting-edge optimization techniques like population-based metaheuristic models, which can quickly generate a solution with acceptable quality. Ant Colony Optimization (ACO) is one the most critical and widely used models among heuristics and meta-heuristics. This book discusses ACO applications in Hybrid Electric Vehicles (HEVs), multi-robot systems, wireless multi-hop networks, and preventive, predictive maintenance

Contemporary forest road management with economic and environmental objectives

One of the basic questions facing transportation planners and road managers is how to provide and maintain a road system that provides efficient access to the forest while limiting adverse effects roads can have on water and soil resources. The purpose of this study is to develop decision support models that will lead to improved economic and environmental efficiency in the management of forest road networks. In particular, I focus on developing techniques to facilitate tradeoff analysis and help landowners identify optimal erosion control policies. Forest roads contribute to accelerated erosion, which can degrade water quality and aquatic habitat. Federal agencies in the Pacific Northwest are actively seeking to remove and/or improve roads in order to restore watershed condition, and private landowners face regulatory restrictions under the Clean Water Act and state forest practice acts. Though the treatment that best achieves management objectives for a single road can often be identified, at larger scales the combination of treatments to assign to a suite of roads can become too large for enumeration. In these circumstances decision aids can and have been used. This dissertation is comprised of five manuscripts that pair industrial engineering and forest engineering principles in order to provide relevant decision support tools to facilitate forest road management. The manuscripts address a range of available treatments, including regular maintenance, upgrading, and road removal. The first chapter describes the challenges associated with erosion control, reviews available road treatments, and summarizes salient applications of decision support for road management, focusing on applications where controlling road-related erosion was an objective. The second chapter introduces a tradeoff analysis framework for controlling road-related erosion. The third chapter presents an algorithm for routing maintenance vehicles (graders) across a forest road network in order to minimize total tour length, a proxy for operating cost. Chapter four extends this work to a multi-objective context, seeking efficient solutions that simultaneously minimize vehicle operating cost plus grading cost and hazard weighted rut depth, a measure of environmental performance. Chapter five develops optimal policies for recycling aggregate from decommissioned forest roads, and demonstrates that recovery and reuse of aggregate can subsidize road removal projects. Chapter six extends this work to a multi-objective context, approximating the efficient frontier for length of road removed and removal cost, and investigating further the potential for aggregate recycling to effectively subsidize decommissioning projects. Chapter seven concludes the dissertation with a review of the preceding chapters

Smart Sustainable Manufacturing Systems

With the advent of disruptive digital technologies, companies are facing unprecedented challenges and opportunities. Advanced manufacturing systems are of paramount importance in making key enabling technologies and new products more competitive, affordable, and accessible, as well as for fostering their economic and social impact. The manufacturing industry also serves as an innovator for sustainability since automation coupled with advanced manufacturing technologies have helped manufacturing practices transition into the circular economy. To that end, this Special Issue of the journal Applied Sciences, devoted to the broad field of Smart Sustainable Manufacturing Systems, explores recent research into the concepts, methods, tools, and applications for smart sustainable manufacturing, in order to advance and promote the development of modern and intelligent manufacturing systems. In light of the above, this Special Issue is a collection of the latest research on relevant topics and addresses the current challenging issues associated with the introduction of smart sustainable manufacturing systems. Various topics have been addressed in this Special Issue, which focuses on the design of sustainable production systems and factories; industrial big data analytics and cyberphysical systems; intelligent maintenance approaches and technologies for increased operating life of production systems; zero-defect manufacturing strategies, tools and methods towards online production management; and connected smart factories

An Investigation to Evaluate the Feasibility of an Intermodal Freight Transport System.

The threat of greenhouse gases and the resulting climate change have been causing concern at international levels. This has led towards new sustainable policies towards reducing the anthropogenic effects on the environment and the population through promoting sustainable solutions for the freight industry. The research was prompted by the growing concerns that were no mode-choice tool to select as an alternative to road freight transport. There were growing concerns that a large percentage of transport related negativities, related various costs and pollution costs, losses arising from traffic accidents, delay costs from congestion and abatement costs due to climate impacts of transport, etc., were not being borne by the user. Economists have defined them as external costs. Internalising these external costs has been regarded as an efficient way to share the transport related costs. The aim of this research was to construct a freight mode choice model, based on total transport costs, as a mode choice substitution tool. This model would allow the feasibility of choosing alternative intermodal system to a primarily ‘road system’. The thesis postulates a novel model in computing total freight transport costs incurred during the total transit of goods along three North European transport corridors. The model evaluated the total costs summing the internal, external and time costs for varied mode choices from unimodal and the second level of intermodal transport systems. The research outcomes have shown the influences of total costs on the shipper and the preferred mode choices from the available mode/route options with sustainable transport solutions. The impacts of such alternatives were evaluated in this research. This will allow the embedding of intermodal infrastructures as sustainable and alternative mode choices for the freight industry

Whole life costing optimisation with integrated logistics support considerations.

It has long been recognised that, in the military sector, the Integrated Logistics Support ILS can significantly enhance system effectiveness and add value to their competitiveness. Hence, it is not surprising that many organisations outside to the military support the ILS adoption to increase their competence level. Even though the ILS underlying theory is general, there is a lack of suitable methodology that facilitates ILS implementation in other industries such as Oil & Gas industry. In particular when considering complex systems with long life-span, the optimisation of maintenance-related activities is important to fulfil system readiness, safety and whole life cost requirements. Modern petroleum equipment like gas turbines and drilling rigs are dependent on readily available maintenance supports in order to maximise their operational ability. Therefore, it has been identified that the study should be conducted to an effective use of ILS with the petroleum industry. In doing so, the usage of the ILS framework as a decision tool for maintenance optimisation is outlined. This framework embraces ILS concepts to support asset managers in developing their maintenance strategies. Level of repair analysis and spare parts management have been identified as potential areas for enhancing the use of ILS. In particular, maintenance optimisation is approached as a trade-off between investment in spare parts level and repair capacity. The developed framework delivers cost-effective support strategies obtained with iterative optimisation algorithm built on heuristics and genetic algorithm techniques. Finally, this algorithm has been implemented into computational algorithms. The framework can be employed to identify the optimum level of spare parts and the optimum amount of repair capacity for multi echelon repair network and multi-indenture systems. The framework has been used to carry out optimisations intended to maximise the availability of gas turbines by varying logistics support parameters. Typical results have shown that a joint optimisation of spare parts and level of repair analysis leads to better results than optimising them separately and emphasises the need for the developed framework. As part of this research, an expert panel validation method has been used to both refine the design of the developed framework and also evaluate its functionality from experienced practitioners within the Algerian petroleum industry. The results of this validation have demonstrated the advantages of integrating spare part management and level of repair analysis LORA to the problem of maintenance optimisation and shown that the framework is able to deliver optimal maintenance supportability decisions. The generic framework developed in this thesis can be seen a novel and comprehensive model for integrating two ILS elements into the operating tool in a manner that improves maintenance support provision, while remaining both flexible and usable; and therefore as a contribution to a better adoption of ILS technique within Algerian Petroleum Industry

Proceedings of the 2nd Conference on Production Systems and Logistics (CPSL 2021)

Proceedings of the CPSL 202

Expanding the Horizons of Manufacturing: Towards Wide Integration, Smart Systems and Tools

This research topic aims at enterprise-wide modeling and optimization (EWMO) through the development and application of integrated modeling, simulation and optimization methodologies, and computer-aided tools for reliable and sustainable improvement opportunities within the entire manufacturing network (raw materials, production plants, distribution, retailers, and customers) and its components. This integrated approach incorporates information from the local primary control and supervisory modules into the scheduling/planning formulation. That makes it possible to dynamically react to incidents that occur in the network components at the appropriate decision-making level, requiring fewer resources, emitting less waste, and allowing for better responsiveness in changing market requirements and operational variations, reducing cost, waste, energy consumption and environmental impact, and increasing the benefits. More recently, the exploitation of new technology integration, such as through semantic models in formal knowledge models, allows for the capture and utilization of domain knowledge, human knowledge, and expert knowledge toward comprehensive intelligent management. Otherwise, the development of advanced technologies and tools, such as cyber-physical systems, the Internet of Things, the Industrial Internet of Things, Artificial Intelligence, Big Data, Cloud Computing, Blockchain, etc., have captured the attention of manufacturing enterprises toward intelligent manufacturing systems