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The modern helicopters are designed with maximum serviceability and long life expectancy to ensure minimum life cycle cost. The purpose of this paper is to present a framework to incorporate the customer requirements on reliability and maintainability (R&M) parameters into the design and development phase of a contemporary helicopter, and to discuss the way to capture operational data to establish and improve the R&M parameters to reduce life cycle cost.

From the analysis, it is established that the reliability and maintainability cost is the major contributor to the life cost. The significant reliability and maintainability parameters which influence R&M cost are identified from analysis. The operational and design data of a contemporary helicopter are collected, compiled and analyzed to establish and improve the reliability and maintainability parameters.

The process depicted in the paper is followed for a contemporary helicopter and substantial amount of life cycle cost reduction is observed with improvement of R&M parameters.

The benefits of this methodology not only reduce life cycle cost but also improve the availability/serviceability through less failure and less time for scheduled maintenance. The methodologies also provide the reliability trends indicating potential area for design improvement.

The proposed approach assists asset managers to reduce the life cycle costs through improvement of R&M parameters.

A substantial number of production assets in the offshore oil and gas industry are facing operation beyond their anticipated design life, thus necessitating a service life extension program in the future. Selection of the most suitable strategy among a wide range of potential options to extend the lifetime of equipment (e.g. re-using, reconditioning, remanufacturing, refurbishing and adding on safety/process control measures) remains a challenging task that involves several technical, economic and organizational complexities. In order to tackle this challenge, it is crucial to develop analytical tools and methods capable of evaluating and prioritizing end-of-life strategies with respect to their associated costs and quantifiable benefits. The paper aims to discuss these issues.

This paper presents a life-cycle cost-benefit analysis approach to identify the most suitable life extension strategy for ageing offshore assets by taking into account all the capital, installation, operational, maintenance and risk expenditures during the extended phase of operation. The potential of the proposed methodology is demonstrated through a case study involving a three-phase separator vessel which was constructed in the mid-1970s.

The results from the application case indicate that the capital expenditure (CapEx) accounts for the largest portion of life cycle cost for the replacement strategy, while risk expenditure (RiskEx) is the major contributor to costs associated with life extension. A sensitivity analysis is also conducted to identify factors having the greatest impact on the optimum life extension solution, including oil price, production rate and money interest rate.

In the past, the decisions about life extension or replacement of in-service equipment were often made in a qualitative way based on experience and judgment of engineers and inspectors. This study presents a “quantitative” framework to evaluate and compare the costs, benefits and risks associated with life extension strategies and subsequently to select the best strategy based on benefit/cost ratios.

To the best of authors’ knowledge, no studies before have applied life cycle assessment and cost-benefit analysis methods to prioritize the potential life extension strategies in the oil and gas industry sector. The proposed approach not only assists decision makers in selecting the most suitable life extension strategy but also helps duty holders reduce the costs corresponding to life extension execution.

This research aims to aid product development managers to estimate the expected cost associated with the development of cost-intensive physical prototypes considering transitions associated with pertinent states of quality of the prototype and corresponding decision policies under the Markovian setting.

The authors evolve two types of optimization-based mathematical models under both deterministic and randomized policies. Under the deterministic policy, the product development managers take certain decisions such as “Do nothing,” “Overhaul,” or “Replace” corresponding to different quality states of prototype such as “Good as new,” “Functional with minor deterioration,” “Functional with major deterioration” and “Non-functional.” Under the randomized policy, the product development managers ascertain the probability distribution associated with these decisions corresponding to various states of quality. In both types of mathematical models, i.e. related to deterministic and randomized settings, minimization of the expected cost of the prototype remains the objective function.

Employing an illustrative case of the operator cabin from the construction equipment domain, the authors ascertain that randomized policy provides us with better decision interventions such that the expected cost of the prototype remains lower than that associated with the deterministic policy. The authors also ascertain the steady-state probabilities associated with a prototype remaining in a particular quality state. These findings have implications for product development budget, time to market, product quality, etc.

The authors’ work contributes toward the development of optimization-driven mathematical models that can encapsulate the nuances related to the uncertainty of transition of quality states of a prototype, decision policies at each quality state of the prototype while considering such facets for all constituent subsystems of the prototype. As opposed to a typical prescriptive study, their study captures the inherent uncertainties associated with states of quality in the context of prototype testing, etc.

The findings from a set of related investigations into construction megaproject management were integrated into models, frameworks and basic guidelines that would help to improve and integrate (1) work packaging, (2) project participant selection and (3) operational management subsystems. More creative approaches to work packaging and participant selection were seen to significantly support construction industry development and the consequent longer‐term benefits in developing countries. A paradigm of ‘technology exchange’ is proposed as the basis of more viable and mutually beneficial joint ventures which would also facilitate the innovative packaging and integrated management of megaprojects in developing countries. Additionally, it is recommended that hitherto isolated initiatives related to quality, safety or dispute resolution/avoidance should be integrated into synergistic management systems which also incorporate built‐in monitoring and evaluation sub‐systems. In turn, the latter would trigger both short‐ and long‐term remedial measures related to improved project packaging, for example, as well as to personnel training and organizational development programmes.

In the last 20 years, e-waste has become a serious issue resulting from an overwhelming amount of electronics consumption. However, there has been limited research on how to decrease such waste in a structured manner. Toward study was to use a simulation methodology to investigate the dynamics of upfront investment in reliability enhancement promoted by performance-based contracting (PBC), based on the number of spare parts and duration of the contract.

The present research first details the relevant mathematical equations and uses game theory to demonstrate the utility for supplier and buyer relationships. Next, the effects of reliability enhancement, spare partsPBC are analyzed using a BlockSim simulation model.

The results indicate strong relationships among system design cost, reliability, availability and service cost. The authors found that investment in reliability increases system availability while reducing total service costs. Furthermore, increasing the spare parts inventory was determined to have less influence on the readiness of highly reliable systems. The findings support the notion that PBC reduces e-waste by increasing system availability, incentivizing upfront investment in reliability growth.

Recognition of these findings in the context of buyer–supplier relationships will help managers better understand the value of upfront reliability investment, reducing maintenance, repair and overhaul requirements, avoiding the need to plan for extra spare parts and minimizing volume and the resulting e-waste.

This study also clarifies the uncertainty associated with upfront investment and provides potential incentives for suppliers.

The main contribution of this study is its use of PBC for e-waste reduction, highlighting the effects of upfront investment in reliability enhancement. The authors applied a game theory model to illustrate the relationship between incentives and upfront investment and demonstrate how increased levels of spare parts can be counterproductive to achieving readiness, reducing inventory and consequent e-waste.

The idea of implementing supply chain management (SCM) principles for the construction industry was embraced by construction stakeholders to enhance the sector's performance. The analysis from the literature revealed that the implementation of SCM in the construction industry enhances the industry's value in terms of cost-saving, time savings, material management, risk management and others. The construction supply chain (CSC) can be managed using the pull or push system. This chapter also discusses the origin and proliferation of SCM into the construction industry. The chapter revealed that the concept of SCM has passed through five different eras: the creation era, the use of ERP, globalisation stage, specialisation stage and electronic stage. The findings from the literature revealed that we are presently in the fourth industrial revolution (4IR) era. At this stage, the SCM witnesses the adoption of technologies and principles driven by the 4IR. This chapter also revealed that the practice of SCM in the construction industry is centred around integration, collaboration, communication and the structure of the supply chain (SC). The forms and challenges hindering the adoption of these practices were also discussed extensively in this chapter.

The heightened state of flux in the construction industry in general and construction procurement strategies in particular, provides welcome opportunities to inject innovative improvements. While some improvements are generated from within the construction industry itself, these evolve sluggishly along prolonged learning curves. These are compared with lessons to be learnt and examples to be drawn from manufacturing in the development of a marketable product. A product development focus is thus advocated in re‐integrating segregated groups and in empowering and inspiring the innovations that are needed to achieve the dramatic productivity gains now demanded from the construction industry.

Benchmarking of best practices has proved useful in the business and manufacturing sectors. However, benchmarking is not established in the construction industry in general and in government organizations in particular. A study of the contractor selection methodologies used by various clients confirms the multiplicity of approaches in practice. This paper aims at identifying some relevant ‘best’ practices and highlighting ‘innovative’ contractor selection approaches that have been used by large public clients. A ‘co‐operative’ and ‘non‐competitive’ conceptual benchmarking model is formulated and presented with a view to encouraging continuous improvement in contractor selection for construction projects.

The concept of modularity has gained considerable traction in technology studies as a way to conceive, describe, and innovate complex systems, such as product design or organizational structures. In the recent literature, technological modularity has often been intertwined with business model innovation, and scholarship has started investigating how modularity in technology affects changes in business models, both at the cognitive and activity system levels. Yet we still lack a theoretical definition of what modularity is in the business model domain. Business model innovation also encompasses different possibilities of modelling businesses, which are not clearly understood nor classified. We ask when, how, and if modularity theory can be extended to business models in order to enable effective and efficient modelling. We distinguish theoretically between modularity for technology and for business models, and investigate the key processes of modularization and manipulation. We introduce the basic operations of business modelling via modular operators adapted from the technological modularity domain, using iconic examples to develop an analogical reasoning between modularity in technology and in business models. Finally, we discuss opportunities for using modularity theory to foster the understanding of business models and modelling, and develop a challenging research agenda for future investigations.

With numerous and ambiguous sets of information and often conflicting requirements, construction management is a complex process involving much uncertainty. Decision makers may be challenged with satisfying multiple criteria using vague information. Fuzzy multi-criteria decision-making (FMCDM) provides an innovative approach for addressing complex problems featuring diverse decision makers’ interests, conflicting objectives and numerous but uncertain bits of information. FMCDM has therefore been widely applied in construction management. With the increase in information complexity, extensions of fuzzy set (FS) theory have been generated and adopted to improve its capacity to address this complexity. Examples include hesitant FSs (HFSs), intuitionistic FSs (IFSs) and type-2 FSs (T2FSs). This chapter introduces commonly used FMCDM methods, examines their applications in construction management and discusses trends in future research and application. The chapter first introduces the MCDM process as well as FS theory and its three main extensions, namely, HFSs, IFSs and T2FSs. The chapter then explores the linkage between FS theory and its extensions and MCDM approaches. In total, 17 FMCDM methods are reviewed and two FMCDM methods (i.e. T2FS-TOPSIS and T2FS-PROMETHEE) are further improved based on the literature. These 19 FMCDM methods with their corresponding applications in construction management are discussed in a systematic manner. This review and development of FS theory and its extensions should help both researchers and practitioners better understand and handle information uncertainty in complex decision problems.