Production Scheduling

Generally speaking, scheduling is the procedure of mapping a set of tasks or jobs (studied objects) to a set of target resources efficiently. More specifically, as a part of a larger planning and scheduling process, production scheduling is essential for the proper functioning of a manufacturing enterprise. This book presents ten chapters divided into five sections. Section 1 discusses rescheduling strategies, policies, and methods for production scheduling. Section 2 presents two chapters about flow shop scheduling. Section 3 describes heuristic and metaheuristic methods for treating the scheduling problem in an efficient manner. In addition, two test cases are presented in Section 4. The first uses simulation, while the second shows a real implementation of a production scheduling system. Finally, Section 5 presents some modeling strategies for building production scheduling systems. This book will be of interest to those working in the decision-making branches of production, in various operational research areas, as well as computational methods design. People from a diverse background ranging from academia and research to those working in industry, can take advantage of this volume

Challenges and complexities in application of LCA approaches in the case of ICT for a sustainable future

In this work, three of many ICT-specific challenges of LCA are discussed. First, the inconsistency versus uncertainty is reviewed with regard to the meta-technological nature of ICT. As an example, the semiconductor technologies are used to highlight the complexities especially with respect to energy and water consumption. The need for specific representations and metric to separately assess products and technologies is discussed. It is highlighted that applying product-oriented approaches would result in abandoning or disfavoring of new technologies that could otherwise help toward a better world. Second, several believed-untouchable hot spots are highlighted to emphasize on their importance and footprint. The list includes, but not limited to, i) User Computer-Interfaces (UCIs), especially screens and displays, ii) Network-Computer Interlaces (NCIs), such as electronic and optical ports, and iii) electricity power interfaces. In addition, considering cross-regional social and economic impacts, and also taking into account the marketing nature of the need for many ICT's product and services in both forms of hardware and software, the complexity of End of Life (EoL) stage of ICT products, technologies, and services is explored. Finally, the impact of smart management and intelligence, and in general software, in ICT solutions and products is highlighted. In particular, it is observed that, even using the same technology, the significance of software could be highly variable depending on the level of intelligence and awareness deployed. With examples from an interconnected network of data centers managed using Dynamic Voltage and Frequency Scaling (DVFS) technology and smart cooling systems, it is shown that the unadjusted assessments could be highly uncertain, and even inconsistent, in calculating the management component's significance on the ICT impacts.Comment: 10 pages. Preprint/Accepted of a paper submitted to the ICT4S Conferenc

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

Application of Lean Principles to Neurosurgical Procedures: The Case of Lumbar Spinal Fusion Surgery, a Literature Review and Pilot Series

BACKGROUND Delivery of higher value healthcare is an ultimate government and public goal. Improving efficiency by standardization of surgical steps can improve patient outcomes, reduce costs, and lead to higher value healthcare. Lean principles and methodology have improved timeliness in perioperative medicine; however, process mapping of surgery itself has not been performed. OBJECTIVE To apply Plan/Do/Study/Act (PDSA) cycles methodology to lumbar posterior instrumented fusion (PIF) using lean principles to create a standard work flow, identify waste, remove intraoperative variability, and examine feasibility among pilot cases. METHODS Process maps for 5 PIF procedures were created by a PDSA cycle from 1 faculty neurosurgeon at 1 institution. Plan, modularize PIF into basic components; Do, map and time components; Study, analyze results; and Act, identify waste. Waste inventories, spaghetti diagrams, and chartings of time spent per step were created. Procedural steps were broadly defined in order to compare steps despite the variability in PIF and were analyzed with box and whisker plots to evaluate variability. RESULTS Temporal variabilities in duration of decompression vs closure and hardware vs closure were significantly different (P = .003). Variability in procedural step duration was smallest for closure and largest for exposure. Wastes including waiting and instrument defects accounted for 15% and 66% of all waste, respectively. CONCLUSION This pilot series demonstrates that lean principles can standardize surgical workflows and identify waste. Though time and labor intensive, lean principles and PDSA methodology can be applied to operative steps, not just the perioperative period

Models Needed to Assist in the Development of a National Fiber Supply Strategy for the 21st Century: Report of a Workshop

This discussion paper reports on a Workshop on Wood Fiber Supply Modeling held October 3-4, 1996 in Washington, DC. The purpose of this discussion paper is to provide an overview of some of the modeling work being done related to timber supply modeling and some of the issues related to the more useful application of wood fiber supply and projections models. This paper includes brief presentations of three commonly used long-term timber projections and forecasting models: the Timber Assessment Market Model (TAMM) of the Forest Service; the Cintrafor Global Trade Model (CGTM) of the University of Washington; and the Timber Supply Model (TSM) of Resources for the Future. Also, issues related to the useful of the models are addressed as well as a discussion of some applications of other timber or fiber projection models. The usefulness of the models are addressed from both a technical perspective and also from the perspective of their usefulness to various model users.

Considering Life Cycle Greenhouse Gas Emissions in Power System Expansion Planning for Europe and North Africa Using Multi-Objective Optimization

We integrate life cycle indicators for various technologies of an energy system model with high spatiotemporal detail and a focus on Europe and North Africa. Using multi-objective optimization, we calculate a pareto front that allows us to assess the trade-offs between system costs and life cycle greenhouse gas (GHG) emissions of future power systems. Furthermore, we perform environmental ex-post assessments of selected solutions using a broad set of life cycle impact categories. In a system with the least life cycle GHG emissions, the costs would increase by ~63%, thereby reducing life cycle GHG emissions by ~82% compared to the cost-optimal solution. Power systems mitigating a substantial part of life cycle GHG emissions with small increases in system costs show a trend towards a deployment of wind onshore, electricity grid and a decline in photovoltaic plants and Li-ion storage. Further reductions are achieved by the deployment of concentrated solar power, wind offshore and nuclear power but lead to considerably higher costs compared to the cost-optimal solution. Power systems that mitigate life cycle GHG emissions also perform better for most impact categories but have higher ionizing radiation, water use and increased fossil fuel demand driven by nuclear power. This study shows that it is crucial to consider upstream GHG emissions in future assessments, as they represent an inheritable part of total emissions in ambitious energy scenarios that, so far, mainly aim to reduce direct CO$_{2}$ emissions

Towards a Spatio-temporal Life Cycle Analysis: a Novel Approach to Consider Local and Regional Inventories

Neglecting dynamic information can impact the results of Life Cycle Assessment studies and wrong conclusions, e.g. in policy making, may be drawn. The long-term vision can be described as the development of a complete Life Cycle Assessment study using one comprehensive spatio-temporal Life Cycle Assessment approach to not only calculate regional and local inventories, but also include a dynamical Life Cycle Impact Assessment to determine environmental impact caused by the regional and spatial inventories. This thesis aims to take steps towards this vision by concentrating on spatio-temporal Life Cycle Inventories. Two spatio-temporal Life Cycle Inventory methods are proposed within this Thesis, both are based on the Enhanced Structural Path Analysis method. The first one includes temporal and spatial information on a local scale and comprises landscape characteristics. Therewith, the dispersion of inventories can be modelled. Results of a case study analysing wheat production show the spatio-temporal dispersion for the example emission of salt in flowing water. The second method uses regional datasets from Ecoinvent to calculate inventories over the entire life cycle. The framework was applied to calculate the CO2-inventories of a 5 MW offshore Wind Turbine over its entire life cycle stages. Results are presented in dynamical emissions maps, showing the accumulation of emissions according to the regional occurrence within the life cycle stages over time. Furthermore, the Enhanced Structural Path Analysis is considered for an optimisation analysis. Limitations of the method are mathematically proven. This includes results that the sum and maximum of the Inventory vector as well as Lifetime of Atmospheric CO2 models can either not be minimised or have restricted optimal solutions. The cumulative output, including and excluding Lifetime of Atmospheric CO2 models are minimal for every inventory vector time-series. The output peaks of the Inventory are minimal if the final demand vector is uniformly distributed. The results are confirmed by simulations for using the 5 MW offshore Wind Turbine case study. The thesis demonstrates that it is possible to implement spatio-temporal information into Life Cycle Assessments. We believe that the proposed methods will improve the traditional Life Cycle Assessments and will help to introduce a framework for a dynamical approach

Multi Agent Systems in Logistics: A Literature and State-of-the-art Review

Based on a literature survey, we aim to answer our main question: “How should we plan and execute logistics in supply chains that aim to meet today’s requirements, and how can we support such planning and execution using IT?†Today’s requirements in supply chains include inter-organizational collaboration and more responsive and tailored supply to meet specific demand. Enterprise systems fall short in meeting these requirements The focus of planning and execution systems should move towards an inter-enterprise and event-driven mode. Inter-organizational systems may support planning going from supporting information exchange and henceforth enable synchronized planning within the organizations towards the capability to do network planning based on available information throughout the network. We provide a framework for planning systems, constituting a rich landscape of possible configurations, where the centralized and fully decentralized approaches are two extremes. We define and discuss agent based systems and in particular multi agent systems (MAS). We emphasize the issue of the role of MAS coordination architectures, and then explain that transportation is, next to production, an important domain in which MAS can and actually are applied. However, implementation is not widespread and some implementation issues are explored. In this manner, we conclude that planning problems in transportation have characteristics that comply with the specific capabilities of agent systems. In particular, these systems are capable to deal with inter-organizational and event-driven planning settings, hence meeting today’s requirements in supply chain planning and execution.supply chain;MAS;multi agent systems

Modular Supply Network Optimization of Renewable Ammonia and Methanol Co-production

To reduce the use of fossil fuels and other carbonaceous fuels, renewable energy sources such as solar, wind, geothermal energy have been suggested to be promising alternative energy that guarantee sustainable and clean environment. However, the availability of renewable energy has been limited due to its dependence on weather and geographical location. This challenge is intended to be solved by the utilization of the renewable energy in the production of chemical energy carriers. Hydrogen has been proposed as a potential renewable energy carrier, however, its chemical instability and high liquefaction energy makes researchers seek for other alternative energy carriers. Ammonia and methanol can serve as promising alternative energy carriers due to their chemical stability at room temperature, low liquefaction energy, high energy value. The co-production of these high energy dense energy carriers offers economic and environmental advantages since their synthesis involve the direct utilization of CO2 and common unit operations. This problem report aims to review the optimization of the co-production of methanol and ammonia from renewable energy. Form this review, research challenges and opportunities are identified in the following areas: (i) optimization of methanol and ammonia co-production under renewable and demand uncertainty, (ii) impacts of the modular exponent on the feasibility of co-production of ammonia and methanol, and (iii) development of modern computational tools for systems-based analysis