For ages, the traditional engineering design of a product, system or service, was basically aimed to improve its dependability, which emphasized its quality, reliability, maintainability and safety. But it never went into the question of where the material used came from, how it was extracted, what were the processes to manufacture it and what are the effects of its use on the environment of our planet and how finally it is disposed of at the end of its useful life? These questions have become quite relevant today, while the population of the world is increasing on one hand and resources of our planet are becoming scarce and costly day by day and the amount of wastages is becoming enormous, it becomes imperative to consider these aspects of sustainability quite seriously in order to meet the demands of our future generations and to protect Earth’s environment from further degradation. Today, we need sustainable design engineering, which is inherent in the definition of performability as is used and propagated in this journal (see the scope of this journal). Performability, in short, is the integration of sustainability principles with dependability. Perfomability Engineering is a holistic interdisciplinary approach to optimally design and engineer products, systems and services that are not only dependable but also sustainable. The era of convention design, which usually would ensure the dependability of a product without any consideration of how the process of production and use of a product influences our environment at various stages of the life cycle of the product, is over. The objective of this journal has been to highlight these aspects of sustainable design of products, systems and services.

A sustainable design envisages that the products, systems, and services would meet the needs of society while striking a balance between economic and environmental interests. Given the challenge of coordinating the complex trade-offs between economic, societal, and environmental factors influenced by design, it can be expected that governments interested in operationalizing sustainable development will begin to legislate the options available to designers. European Union has been quite conscious of its responsibility in this respect and has brought forward some important legislation in the form of Directives on Waste Electric and Electronic Equipment (WEEE), Restrictions on Hazardous Substances (RoHS), and End of Life Vehicles (ELVs). These steps will surely accelerate the process of sustainable development. The initiatives like dematerialization (minimum use of material), minimization of energy use at all stages of life cycle as well as use of renewable source of energy, minimization of wastes at all stages of life cycle, strategy of recycling, reuse, remanufacturing and the extension of life through easy maintenance or renovation, material valorisation and disposal after end of life, are some of the steps that help achieve a sustainable product design.

This year we have brought out two special issues on sustainability. The theme of June 2014 issue of IJPE was on Balancing Technology, Environment and Lifestyles. We also realize that effort to propagate sustainability in design must begin with the students of today so that they can become accomplished sustainability designers in due course. Realizing this, it was considered appropriate to encourage engineering graduates and postgraduate students to submit their papers to the special issue of June 2014. This issue was very well Guest Edited by two well-known professors and a post graduate student (which was a unique experience for them) on the basis of symposium conducted with participation of post graduate studentsfrom the European nations.

The Theme of this issue was deliberately chosen to initiate a beginning in the area of promoting sustainability design. The Guest Editors did their best to present a status report on the subject and it is hoped that with the present issue a beginning has been made to introduce the subject of sustainability design to conventional designers and engineering students who are familiar only with conventional design and would like to know the direction in which the engineering community is moving today. I like to thank the Guest Editors of this issue, Dr. Claver Diallo and Dr. Uday Venkatadri of Industrial Engineering Department of Dalhousie University, and Dr. Daoud Ait-Kadi, Department of Mechanical Engineering of Laval University, Canada, who have worked on the issue to guarantee quality papers. My thanks are also due to reviewers, who helped in maintain timeliness in reviewing process. I would also like to thank the authors whose contributions are included in this issue and maintained the dead lines. It is hoped that this issue of IJPE will generate further interest in sustainability design and provide impetus to research in this important area of 21^st Century and we will continue to bring out such special issues in the future as well.

In today's highly competitive market, performance optimization has become an important factor in attaining competitiveness, profitability and increased customer satisfaction. Combined with the demand and regulatory push for sustainable products, it has become imperative to analyze and optimize systems performance over their lifecycle: from the design stage to the disposal stage (from cradle to grave) including end of life treatment such as reconditioning and reuse or recycle.

In this issue of the International Journal of Performability Engineering (IJPE), we bring out seven papers dealing with problems relating to the Design of Products, Systems and Services for Dependability and Sustainability. According to the Handbook of Performability Engineering (Ed. Krishna B. Misra, Springer Verlag, 2008), sustainability requirements should be addressed along with other factors such as quality, reliability, maintenance and safety, for optimum performance. The objective is to produce products, systems and services that have built in quality, reliability, maintainability and safety, and are produced through clean production and technologies that result in minimal pollution, require minimum raw materials and energy and safe to dispose of or reuse at the end of their lives.

The papers included in this issue have gone through a rigorous two-stage blind-review process by the guest-editors and reviewers selected from amongst the best experts in performability engineering. Our goal is to bring to the readership of IJPE some key papers that will kick-start a vibrant and fruitful stream of research and industry papers in the area of sustainability and dependability.

In the first paper titled “State of the Art on Dependability and Sustainability across the Sustainable Value Chain”, Navin Chari et al. review the most recent advances in sustainability and dependability throughout the value chain. They focus on dependability factors within the green supply chains, life cycle analyses, and EcoDesign methodologies. They then propose a new sustainable product life cycle framework to represent key lifetime stages of sustainable products covering the collection, remanufacturing, reuse, and end-of-life support service systems. A section is devoted to the important issues of upgrade, maintenance, and warranty models in remanufacturing They conclude their paper with a discussion of future research challenges in this field.

In the second paper of the issue, viz., Reliability Analysis and Optimal Mixture Strategy for a Lot composed of New and Reconditioned Systems, Diallo et al., introduce and study the shape and the behavior of the failure rate of a mixture of two populations of components with the same distribution but different ages. This type of mixture is encountered in industrial settings when new and reconditioned systems are mixed together in remanufacturing or for maintenance operations. The conditions under which such a mixture of increasing failure rate components can result in a population with modified bathtub-shaped failure rate are derived. Through an illustrative example, they show that cost-optimal mixture strategies can be derived when reconditioned parts are mixed with new ones in remanufacturing or maintenance.

In the third paper by A. Jodejko-Pietruczuk and M. Plewa, viz., Component Rejuvenation in Production with Reused Elements, the authors present several models to estimate the cost-effectiveness of strategies for the reuse of returned elements in the production of new products. Their models are built for two-component systems and show the impacts that the reliability and cost of each component has on the ultimate remanufacturing decisions.

The fourth paper by Renyan Jiang and Yang Guo develops a robust non-parametric method to estimate the failure intensity function based on the failure processes observed from a single system, or several independent and identical systems, in estimating failure intensity of a repairable system, to decide on its preventive maintenance or retirement. After examining a large number of real-world datasets published in the literature, the authors found that the intensity function of repairable systems is typically of a roller-coaster curve shape. Jiang and Guo also provide several examples of this type of failure pattern along with possible causes. The usefulness of this method for planning the preventive maintenance and determining the retirement time of repairable products is also illustrated. A section is entirely devoted to the significance of this method for sustainability.

The fifth paper by A. Canal Marques titled “Teaching Sustainability Design of Products to Engineering Students” presents the result of a real-life teaching experiment. In this experiment, engineering students were taught how to select materials in the design phase to sustainably cover all stages of the life cycle of these products. The results show the complexity and importance of proper selection of materials and processes for sustainability.

The sixth paper “Dependent Systems Reliability Estimation by Structural Reliability Approach” by E. Kostandyan and J. S?rensen develops a method for dependent systems reliability estimation, where the leading failure mechanism(s) is described based on physics of failure model(s). Dependency is considered for both statistical and failure effect correlations. The proposed method can be used for calibration of limit state functions based on the test data availability and can easily be extended for dependent systems reliability estimation with non-identical components. It can also be used in various decision-making problems such as remanufacturing, when reuse alternatives depend on the system’s residual lifetime.

The seventh and last paper by H. Aoudjit et al. titled “Replacement Scheduling of a Fleet of Hydroelectric Generators: A Case Study” presents a framework to determine optimal maintenance planning of a fleet of complex and independent systems. Their framework uses proportional hazard model to characterize the failure rates of components and the effects of the environmental conditions and the load levels. A nonlinear program is developed to minimize the fleet maintenance cost under age replacement policy of its components and a set of organizational and technical constraints. Lindo API and NOMAD are used to solve the nonlinear model. The framework is applied to set a preliminary plan to overhaul a fleet of 90 hydroelectric generators in 6 power plants over 50 years for Hydro-Quebec.

The Guest Editors would like to thank all the authors for their contributions, and the reviewers for their dedication and the timely feedback provided to contributing authors of this special issue. The Guest Editors would also like to thank Prof. Krishna B. Misra, the Editor-In-Chief of IJPE, who was very helpful in the editing process as well as being a great and continuing supporter of performability knowledge dissemination.

Daoud Ait-Kadi is currently a full professor at the mechanical engineering department and director of graduate studies in industrial engineering at Laval University in Canada. He received his Bachelor’s degree in mechanical engineering from Ecole Mohammadia d’Ingénieurs in 1973, a Master of Science in industrial engineering from Ecole Polytechnique de Montreal in 1980 and a Ph.D. in industrial engineering, operations research and computer science from Montreal University in 1985. His research interests include production and operations management, reliability engineering, maintenance management, life cycle engineering and reverse logistics and spare parts management. He has authored many papers published in IEEE Transactions on Reliability, Naval Research Logistics, IJPR, IJPE, RESS, EJPR, JQME. He coauthored a textbook on stochastic processes (2004), a Handbook of maintenance management and engineering (2009) and two other books on replacement strategies and reverse logistics. He is currently involved in many industrial projects in automotive, aerospace, telecommunications, forest products, electronics and food industries. He is a senior member of IEEE and IIE. He is also a resident member of Hassan II Academy of Sciences and Technology (Morocco). Email: Daoud.Aitkadi@gmc.ulaval.ca

Uday Venkatadri (Ph.D., P.Eng) is an Associate Professor and the Head of the Department of Industrial Engineering at Dalhousie University in Halifax, Nova Scotia. He has taught at Dalhousie University since July 2001. Before joining Dalhousie, he was a Lead Architect for supply chain planning products at Baan. He has also worked as a Research Associate at Université Laval in Québec City. He holds a Ph.D. in Industrial Engineering from Purdue University, a Master of Science degree in Industrial Engineering from Clemson University, and a Bachelor’s degree in Mechanical Engineering from IIT-BHU, Varanasi, India.

His research interests are in facilities planning, production planning and control, and supply chain management. He teaches courses in these areas as well as operations research, modeling of industrial systems, information systems, algorithms, and quality control. He has published in journals such as the International Journal of Advanced Manufacturing Technology, International Journal of Peformability Engineering, Production Planning and Control, International Journal of Production Economics, European Journal of Operations Research, IIE Transactions, International Journal of Production Research, Journal of Manufacturing Systems, and Management Science,. He is a senior member of the Institute of Industrial Engineers (IIE), a member of the Canadian Operational Research Society (CORS) and a member of Engineers Nova Scotia.

His current research has been focused on production systems design. He is interested in incorporating congestion effects in production planning as well as multi-objective supply chain network design. He is working on product placement strategies to improve warehouse operations and continues to work in facilities design including but not limited to the block layout problem, multi-objective facilities design, and recourse issues in stochastic and dynamic facility layout problems. Email: uday.venkatadri@dal.ca

Claver Diallo Ph.D., P.Eng, is an Associate Professor in the Department of Industrial Engineering at Dalhousie University. He received the B.Eng. (1995), M.A.Sc. (2005), and Ph.D. (2006) degrees in mechanical engineering from Université Laval, Québec, Canada. From 1996 to 1999, he worked as a Field Engineer for Schlumberger Oilfield Services. His research interests include maintenance and availability optimization; inventory control; sustainable design; life cycle engineering; and dependability engineering. Email: cd@dal.ca

This paper reviews recent and relevant literature on the role of performability across the sustainable value chain by first introducing pertinent material in green supply chains, life cycle analyses, and EcoDesign methodologies. A new sustainable product life cycle framework is then proposed to represent key lifetime stages of sustainable systems. New research in performability is covered across the value chain of a green enterprise regarding the collection, remanufacturing, reuse, and end-of-life support service systems. Finally, future research challenges in this field are identified and discussed.

In this paper, we introduce and study the shape and the behavior of the failure rate of a mixture of two populations of components with the same distribution but different ages. This type of mixture is encountered in industrial settings when new and reconditioned systems are mixed together in remanufacturing or for maintenance operations. The conditions under which such a mixture of increasing failure rate components can result in a population with modified bathtub-shaped failure rate are derived. A cost-optimal mixture strategy is developed to illustrate a successful use of new and reconditioned parts in maintenance.

Recapturing value from used goods and wastes has recently become one of the companies’ key area of interest. Reusing of products can bring direct advantages because company uses recycled materials or recovered elements instead of expensive raw materials and new components. Reusing of products has become a factor of competitiveness for modern companies. This relates primarily to manufacturers who are obligated to collect their products, which have failed during warranty period. The main objective of this paper is to present models that allow to estimate cost-effectiveness of reusing the returned elements in new production.

Industrial equipment is usually repairable. Reliability of repairable systems depends on maintenance actions, and is characterized by mean cumulative function or failure intensity function of failure processes. Evolution trend of the failure intensity function is called the system-level failure pattern in the literature. The failure pattern plays an important role in preventive maintenance decision analysis. The purpose of this paper is to develop a robust non-parametric method to estimate the failure intensity function based on the failure processes observed from a single system or several independent and identical systems. After examining a large number of real-world datasets published in the literature, it is found that the intensity function of repairable systems is typically of roller-coaster curve shape. This type of failure pattern is illustrated and the possible causes are discussed. The usefulness for planning the preventive maintenance and determining the retirement time of repairable products is also illustrated.

Today we are producing a large number of industrial products and generating considerable volume of waste and these require an increasing area of the dumps and landfills at the end of the product life. Therefore it is necessary that among other things, we need accurate information about materials, manufacturing processes and assessment of environmental impact. In developing a sustainable product, the life cycle analysis plays an important role which at the same time is not an easy task to accomplish. The life cycle assessment in fact plays a key role to decide the best alternatives in the selection of materials and processes for a product. There exist several software to carry out life cycle assessment (LCA). In this article our aim is to discuss the material selection process for products and explore to carry out an LCA for some products of low technological complexity. Since Engineering students of today are going to be product designers of 21st Century, they must learn to select right materials and processes during the design phase. The results presented in this article highlight the complexity and importance of proper selection process of materials for sustainability.

Estimation of system reliability by classical system reliability methods generally assumes that the components are statistically independent, thus limiting its applicability in many practical situations. A method is proposed for estimation of the system reliability with dependent components, where the leading failure mechanism(s) is described by physics of failure model(s). The proposed method is based on structural reliability techniques and accounts for both statistical and failure effect correlations. It is assumed that failure of any component is due to increasing damage (fatigue phenomena) and the component lifetimes follow some continuous and non-negative cumulative distribution functions. An illustrative example utilizing the proposed method is provided, where damage is modeled by a fracture mechanics approach with correlated components and a failure assessment diagram is applied for failure identification. Application of the proposed method can be found in many real world systems.

This paper presents a framework to determine optimal maintenance planning of a fleet of complex and independent systems. They are made up of several major components which operate in different environment conditions, and are built with different technologies. This framework uses proportional hazard model (PHM) to characterize the failure rates of components and the effects of the environmental conditions and the load levels. A nonlinear program is developed to minimize the fleet maintenance cost under age replacement policy of its components and a set of organizational and technical constraints. Lindo API and NOMAD are used to solve the nonlinear model. The framework is applied to set a preliminary plan to overhaul a fleet of 90 hydroelectric generators in 6 power plants over 50 years. Sensitivity and performance indexes are built to interpret the optimization results in two settings: normal and 50% increase in load.

Traditionally, the quality of product is not incorporated in the newsvendor problem. One approach to ensure the quality of the product is through process targeting. Selection of process mean is expected to determine production conforming rate and affects the newsvendor decision regarding the production lot size. The purpose of this paper is to integrate those two important issues, namely, process mean selection and production lot size for a newsvendor who produces the item at a finite rate. The newsvendor uses raw material to produce the item to satisfy a stochastic demand which follows a general distribution. The amount of raw material received by an item is uncertain and follows a normal distribution. It is assumed that the performance variable of the product has a lower specification limit, and the items that do not conform to the specification limit are scrapped with no salvage value. The expected total cost which consists of the following components: acquisition cost, production cost, underage cost, and overage cost is established. Upper and lower bounds on the optimal process mean are determined and a simple procedure to solve the model is devised. Sensitivity analysis is conducted to investigate the effect of the parameters of the proposed model.

Aviation components are considered repairable and subjected to maintenance actions at various levels. The paper discusses general renewal process for an aero engine as repairable component. Reliability parameters are estimated using Generalized Renewal process (GRP) Maximum Likelihood Estimators (MLEs), by collecting field data from three producers of the aero engine. The current practice designates repairable components, as high failure rate components (HFRC) based on the number of unscheduled failures at Repair depots. A methodology is developed to designate HFRC based on Availability. Further, decisions for review of maintenance policies are presented by formulating a maintenance model based on HFRC declaration. The overall capabilities of GRP model, HFRC model and Maintenance models have been evaluated through numerical examples and validated with the existing field conditions.

This paper uses a discrete event simulation based direct method that allows an availability requirement to be used to predict required logistics, design and operation parameters. Parameters that affect both downtime and uptime are addressed in this paper.

Bearings are the key components in most of rotating machineries. Their failures can lead to catastrophic disasters. The accuracy of remaining useful life (RUL) prediction has a great influence on the preventive maintenance activity. RUL prediction based on standard back propagation neural network (BPNN) already exists. However, training standard BPNN needs more time and sometimes it may converge to local optima which can have contrary influence on the accuracy. Existing BPNN improving works used dynamic learning rate, momentum item and utilized genetic algorithms or other random researching algorithm to optimize the adjustment of connect weights in the network. In this paper, an improved BPNN based on Levenberg-Marquardt algorithm and momentum item is proposed. It can predict the bearing’s RUL with a good performance. Finally, the bearing simulation life data sets are used to validate the proposed method. The results show that the prediction accuracy of the proposed method is superior to other existing BPNNs.

We use Markov chains to compare run lengths of Poisson process individuals control charts with and without runs rules. Evidence quantifies the advantage of runs rules for certain cost structures z = C_a / C_b, where C_a is the cost of a Type I error, and C_b is the cost of a Type II error, and different shifts from in-control parameter l₁ to out-of-control parameter l₂.