6,689 research outputs found
Decision Tools Regarding Time Constraints Violation in Manufacturing Workshops
This paper is dedicated to the study of constraints violation in manufacturing workshops with time constraints. In such systems, every operation duration is included between minimal and maximal values. P-time Petri nets are used for modeling. A new theorem is introduced, constituting a decision tool about the occurrence of constraints violation at the level of a synchronization transition when various types of time disturbances occur. It shows the robustness properties of a manufacturing system on a range that may include delay and advance disturbances. The theoretical result is illustrated step by step on a given workshop. Two other lemmas are elaborated contributing to the study of the constraints violation problem. The final goal is to generalize the robustness property towards simultaneous occurrence of two delays at two points of the system, each having its own robustness range
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An Assessment of PIER Electric Grid Research 2003-2014 White Paper
This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014
The first ICASE/LARC industry roundtable: Session proceedings
The first 'ICASE/LaRC Industry Roundtable' was held on October 3-4, 1994, in Williamsburg, Virginia. The main purpose of the roundtable was to draw attention of ICASE/LaRC scientists to industrial research agendas. The roundtable was attended by about 200 scientists, 30% from NASA Langley; 20% from universities; 17% NASA Langley contractors (including ICASE personnel); and the remainder from federal agencies other than NASA Langley. The technical areas covered reflected the major research programs in ICASE and closely associated NASA branches. About 80% of the speakers were from industry. This report is a compilation of the session summaries prepared by the session chairmen
Wireless industrial monitoring and control networks: the journey so far and the road ahead
While traditional wired communication technologies have played a crucial role in industrial monitoring and control networks over the past few decades, they are increasingly proving to be inadequate to meet the highly dynamic and stringent demands of today’s industrial applications, primarily due to the very rigid nature of wired infrastructures. Wireless technology, however, through its increased pervasiveness, has the potential to revolutionize the industry, not only by mitigating the problems faced by wired solutions, but also by introducing a completely new class of applications. While present day wireless technologies made some preliminary inroads in the monitoring domain, they still have severe limitations especially when real-time, reliable distributed control operations are concerned. This article provides the reader with an overview of existing wireless technologies commonly used in the monitoring and control industry. It highlights the pros and cons of each technology and assesses the degree to which each technology is able to meet the stringent demands of industrial monitoring and control networks. Additionally, it summarizes mechanisms proposed by academia, especially serving critical applications by addressing the real-time and reliability requirements of industrial process automation. The article also describes certain key research problems from the physical layer communication for sensor networks and the wireless networking perspective that have yet to be addressed to allow the successful use of wireless technologies in industrial monitoring and control networks
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High-Performance Integrated Window and Façade Solutions for California
The researchers developed a new generation of high-performance façade systems and supporting design and management tools to support industry in meeting California’s greenhouse gas reduction targets, reduce energy consumption, and enable an adaptable response to minimize real-time demands on the electricity grid. The project resulted in five outcomes: (1) The research team developed an R-5, 1-inch thick, triplepane, insulating glass unit with a novel low-conductance aluminum frame. This technology can help significantly reduce residential cooling and heating loads, particularly during the evening. (2) The team developed a prototype of a windowintegrated local ventilation and energy recovery device that provides clean, dry fresh air through the façade with minimal energy requirements. (3) A daylight-redirecting louver system was prototyped to redirect sunlight 15–40 feet from the window. Simulations estimated that lighting energy use could be reduced by 35–54 percent without glare. (4) A control system incorporating physics-based equations and a mathematical solver was prototyped and field tested to demonstrate feasibility. Simulations estimated that total electricity costs could be reduced by 9-28 percent on sunny summer days through adaptive control of operable shading and daylighting components and the thermostat compared to state-of-the-art automatic façade controls in commercial building perimeter zones. (5) Supporting models and tools needed by industry for technology R&D and market transformation activities were validated. Attaining California’s clean energy goals require making a fundamental shift from today’s ad-hoc assemblages of static components to turnkey, intelligent, responsive, integrated building façade systems. These systems offered significant reductions in energy use, peak demand, and operating cost in California
Appropriability mechanisms, innovation, and productivity: evidence from the UK
We use an extended version of the well-established Crepon, Duguet, and Mairesse model [1998. “Research, Innovation and Productivity: An Econometric Analysis at the Firm Level.” Economics of Innovation and New Technology 7 (2): 115–158] to model the relationship between appropriability mechanisms, innovation, and firm-level productivity. We enrich this model in three ways: (1) We compare estimates obtained using a broader definition of innovation spending to those that use R&D spending. (2) We assume that a firm simultaneously innovates and chooses among different appropriability methods to protect the innovation. (3) We estimate the impact of innovation output on firm productivity conditional on the choice of appropriability mechanism. We find that firms that innovate and rate formal methods for the protection of intellectual property highly are more productive than other firms, but that the same does not hold in the case of informal methods of protection, except possibly for large firms as opposed to SMEs. We also find that this result is strongest for firms in the services, trade, and utility sectors, and negative in the manufacturing sector
Decentralized Robust Capacity Control of Job Shop Systems with Reconfigurable Machine Tools
Manufacturing companies are confronted with various challenges from the perspective of customers individual requirements concerning variations of types of products, quantities and delivery dates. This renders the manufacturing process to be more dynamic and complex, which may result in bottlenecks and unbalanced capacity distributions. To cope with these problems, capacity adjustment is an effective approach to balance capacity and load for short or medium term fluctuations on the operational layer. Particularly, new technologies and algorithms need to be developed for the implementation of capacity adjustment. Reconfigurable machine tools (RMTs) and operator-based robust right coprime factorization (RRCF) provide an opportunity for a new capacity control strategy. Therefore, the main purpose of the research is to develop an effective machinery-oriented capacity control strategy by incorporating RMTs and RRCF for a job shop system to deal with volatile customer demands
Establishing a best practice model of supplier relationship management (SRM) for multinational manufacturing companies in the European transportation industry
Purpose/objectives: The research deals with establishing a best practice model in SRM for manufacturing companies in the European transportation industry. The objective of the thesis is to identify schools of thought in SRM, to highlight the causal factors for supply disruptions and to
outline how supply disruptions can be anticipated, managed and prevented. The identified best practices shall be categorized and utilized to establish a best practice model for the respective sector. The purpose is to show how supply chain resilience can be accomplished in global and complex supply chains by means of proactive SRM.
Design/methodology/approach: The empirical part of the research has been conducted with a qualitative and multiple approach over a period of more than two years. The paper examines best practice elements through a systematic literature review combined with semi-structured interviews
involving senior managers in SRM in the European transportation industry. Two case studies have been included for confirming or disconfirming the best practice elements. The empirical part has been divided into four phases: (1) verifying or falsifying the appropriateness of the research questions, (2) best practice identification and categorization, (3) confirmation or disconfirmation of
best practices in SRM, and (4) refining best practice elements.
Findings: The findings represent a significant contribution on how to deal with complex and global supply networks. They will help researchers and practitioners faced with the task of setting up supplier relationships. Furthermore, the findings can be applied when establishing an overall best
practice framework and SRM model.
Research limitations/implications: The research focuses on establishing a best practice SRM model for multinational manufacturing companies in the European transportation industry. The model has not yet been implemented. Therefore, implementation and application to other industries will have to be the subject of further research
Design of a Business Resilience Model for Industry 4.0 Manufacturers
For Industry 4.0, characterized by a high level of complexity due to the network integration of productions, manufacturers have to take radical steps to transform their organizations enabling intelligent industrial operations. As this transformation is accompanied by unforeseen risks and extreme events, organization must build up resilience to withstand them. This research paper develops a practice-oriented model of business resiliency for Industry 4.0 manufacturers. A literature research was performed to illustrate the absence of research in information systems (IS). For a better understanding of the challenges organizations face, a study among 15 experts from Europe was performed. The obtained challenges, requirements and solutions were clustered and used to develop a resilience model. The model is divided into six major components which are used to achieve six resilience characteristics. The developed model enables organizations to get a holistic and practical overview about the transformation they face while adopting to Industry 4.0
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