Maintenance engineering

Abstract: A predictive-maintenance structure for a gradually deteriorating single-unit system (continuous time/continuous state) is presented in this paper. The proposed decision model enables optimal inspection and replacement decision in order to balance the cost engaged by failure and unavailability on an infinite horizon. Two maintenance decision variables are considered: the preventive replacement threshold and the inspection schedule based on the system state. In order to assess the performance of the proposed maintenance structure, a mathematical model for the maintained system cost is developed using regenerative and semi-regenerative processes theory. Numerical experiments show that the s-expected maintenance cost rate on an infinite horizon can be minimized by a joint optimization of the replacement threshold and the a periodic inspection times. The proposed maintenance structure performs better than classical preventive maintenance policies which can be treated as particular cases. Using the proposed maintenance structure, a well-adapted strategy can automatically be selected for the maintenance decision-maker depending on the characteristics of the wear process and on the different unit costs. Even limit cases can be reached: for example, in the case of expensive inspection and costly preventive replacement, the optimal policy becomes close to a systematic periodic replacement policy. Most of the classical maintenance strategies (periodic inspection/replacement policy, systematic periodic replacement, corrective policy) can be emulated by adopting some specific inspection scheduling rules and replacement thresholds. In a more general way, the proposed maintenance structure shows its adaptability to different possible characteristics of the maintained single-unit system.

Abstract: Karl R. Haapala 1 School of Mechanical, Industrial, and Manufacturing Engineering, Oregon State University, 204 Rogers Hall, Corvallis, OR 97331 e-mail: Karl.Haapala@oregonstate.edu Fu Zhao School of Mechanical Engineering, Division of Environmental and Ecological Engineering, Purdue University, 585 Purdue Mall, West Lafayette, IN 47907 e-mail: fzhao@purdue.edu Jaime Camelio Department of Industrial and Systems Engineering, Virginia Polytechnic Institute and State University, 235 Durham Hall, Blacksburg, VA 24061 e-mail: jcamelio@vt.edu John W. Sutherland Division of Environmental and Ecological Engineering, Purdue University, 322 Potter Engineering Center, West Lafayette, IN 47907 e-mail: jwsuther@purdue.edu Steven J. Skerlos Department of Mechanical Engineering, University of Michigan, 2250 GG Brown Building, Ann Arbor, MI 48105 e-mail: skerlos@umich.edu David A. Dornfeld Department of Mechanical Engineering, University of California, 6143 Etcheverry Hall, Berkeley, CA 94720 e-mail: dornfeld@berkeley.edu I. S. Jawahir Department of Mechanical Engineering, University of Kentucky, 414C UK Center for Manufacturing, Lexington, KY 40506 e-mail: jawahir@engr.uky.edu A Review of Engineering Research in Sustainable Manufacturing Sustainable manufacturing requires simultaneous consideration of economic, environmen- tal, and social implications associated with the production and delivery of goods. Funda- mentally, sustainable manufacturing relies on descriptive metrics, advanced decision- making, and public policy for implementation, evaluation, and feedback. In this paper, recent research into concepts, methods, and tools for sustainable manufacturing is explored. At the manufacturing process level, engineering research has addressed issues related to planning, development, analysis, and improvement of processes. At a manufac- turing systems level, engineering research has addressed challenges relating to facility operation, production planning and scheduling, and supply chain design. Though economi- cally vital, manufacturing processes and systems have retained the negative image of being inefficient, polluting, and dangerous. Industrial and academic researchers are re- imagining manufacturing as a source of innovation to meet society’s future needs by under- taking strategic activities focused on sustainable processes and systems. Despite recent developments in decision making and process- and systems-level research, many chal- lenges and opportunities remain. Several of these challenges relevant to manufacturing process and system research, development, implementation, and education are highlighted. [DOI: 10.1115/1.4024040] Andres F. Clarens Department of Civil and Environmental Engineering, University of Virginia, D220 Thornton Hall, Charlottesville, VA 22904 e-mail: aclarens@virginia.edu Jeremy L. Rickli Department of Industrial and Systems Engineering, Virginia Polytechnic Institute and State University, 217 Durham Hall, Blacksburg, VA 24061 e-mail: jlrickli@vt.edu Corresponding author. Contributed by the Manufacturing Engineering Division of ASME for publication in the J OURNAL OF M ANUFACTURING S CIENCE AND E NGINEERING . Manuscript received July 11, 2012; final manuscript received March 4, 2013; published online July 17, 2013. Editor: Y. Lawrence Yao. Manufacturing and Sustainability The concept of sustainability emerged from a series of meetings and reports in the 1970s and 1980s, and was largely motivated by environmental incidents and disasters as well as fears about Journal of Manufacturing Science and Engineering C 2013 by ASME Copyright V AUGUST 2013, Vol. 135 / 041013-1 Downloaded From: http://manufacturingscience.asmedigitalcollection.asme.org/ on 07/09/2014 Terms of Use: http://asme.org/terms

Abstract: The large growth in the wind power industry in the past years mainly focuses on a growing market and the development of large turbines and offshore farms. The high technical availability of wind turbines comes with a greater need for frequent maintenance. Current maintenance planning is not optimized, and it is possible to make maintenance more efficient. Condition monitoring systems (CMS) could resolve the growing wind power industry's need for better maintenance management and increased reliability. Such systems are commonly used in other industries. CMS could continuously monitor the performance of the wind turbine parts and could help determine specific maintenance timing. This paper presents a life cycle cost (LCC) analysis with strategies where CMS improved maintenance planning for a single wind turbine onshore and a wind farm offshore. Case studies are based on real data from Olsvenne2 at Naumlsudden (Gotland, Sweden) and Kentish Flats, in the U.K. The main conclusion is that CMS benefits maintenance management of wind power systems. Improvements can be especially shown for offshore wind farm maintenance planning