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TCO Evaluation in Physical Asset Management: Benefits and Limitations for Industrial Adoption
Abstract
Nowadays, the evaluation of the total cost of ownership (TCO) of an asset for supporting informed decision-making both for investments and managerial issues within the asset management framework is gaining increasing attention in industry. Nevertheless its application in practice is still limited. The aim of this paper is to analyze the benefits and limitations of the adoption of TCO evaluation in asset management. Based on a literature review, the paper defines a framework that categorizes the benefits and potential applications that a TCO model can have for different stakeholders. Together with that, industry related issues that influence its implementation are also considered. Finally, empirical evidences are analyzed through a multiple case study to understand if those benefits are recognized in practice and which are the limitations for the practical adoption of a TCO model that should allow exploiting such benefits.
... The selection of the data collection methods depends on the kind of information the researcher intends to retrieve, from whom and under what circumstances (Robson 2002). Due to the nature of Action Research and Case Study research the techniques being used are mostly qualitative. ...
... The analysis of work documents, in form of books, handbooks, magazines, notices, letters and even non-written material (Robson 2002) such as videos or CAD models, complemented the shadowing activity. This opportunity contributed to the refinement of the methodological approach, mainly by highlighting discrepancies between the processes represented in the internal company and those described by the interviewees. ...
... Interviews have been considered a primary data collection approach in the research. They allow collecting and comparing statements from different informants, and give the freedom to explore the subjective differences of opinions in detail (Robson 2002) (Yin 2009). ...
The increasing globalization of business over the past two decades is driving manufacturing
industries to find new competitive edges, such as developing solutions which encompass
products, services and systems in order to satisfy more sophisticated demands. Such an
integrated development approach requires engineers to adopt a more holistic perspective
when making decisions in the early design stages, taking into consideration both tangible
and intangible aspects of value.
Design requirements, the main assessment criteria used to evaluate design concepts, are
found in this work to give a partial understanding about the stakeholders’ needs and
expectations to be met. This limits the capacity to promote a whole lifecycle perspective
about value when making decisions, and the ability to trade softer aspects with more factual
dimensions, such as technical performances or manufacturing costs.
The notion of ‘value’ is suggested to develop evaluation criteria that clarify the context in
which requirements are generated. A preference for a model-based approach for value
assessment emerges from the study, since the use of models is well established in the
engineers’ current working practice. This thesis benchmarks present value modelling
strategies, such as Value Driven Design (VDD). The majority of VDD approaches stress
mathematical optimization of financial objective functions, which are found to have little
meaning in conceptual design, where data and information are poorly mature. This thesis
proposes instead the application of value models to enhance shared awareness among the
design team about the context behind the face value of design requirements. Value models
are intended to act as boundary objects, facilitating cross-boundary discussion and
negotiation.
This thesis proposes a methodology for value assessment, combining approaches developed
during the empirical studies with concepts available in literature. The methodology
transitions between a qualitative and quantitative assessment loops. The qualitative
assessment loop is based on structuring a set of criteria extracted and translated from
customers and stakeholders, against which design alternatives are computed using a baseline
design as a reference. The quantitative value assessment loop is based on a breakdown of
the customer lifecycle activities, and the value of a design alternative is computed using a
functional model, in order to obtain a single indicator to assess the monetary benefits of
design alternatives.
The prototype of a qualitative value model is investigated through experiments in design
sessions, using a combination of protocol analysis and ethnography. The results from the
protocol analysis support the hypothesis that the value model enhances the discussion about
the design problem. The ethnographic study highlights the role of a value model as a more
effective boundary object than traditional representations, such as a requirements checklist.
The quantitative value model has been presented to industrial practitioners in a focus group
and qualitative feedback has been gathered, highlighting its potential and suggesting future
work.
... However, when comparing the cost among projects, the productivity loss should not be neglected [23]. It is recognized that when the asset fails, the potential output gains lost should be quantified since the asset is out of service [24,25]. Moreover, additional resources are utilized to maintain a smooth manufacturing process in order to ensure operational reliability [26]. ...
... Moreover, additional resources are utilized to maintain a smooth manufacturing process in order to ensure operational reliability [26]. In addition, substandard product quality or reduced productivity may cause a huge amount of waste [25]. Furthermore, some business uncertainties and decision risks can lead to production disruption, leaving equipment and workers waiting [27]. ...
Within the context of the large-scale application of industrial robots, methods of analyzing the life-cycle cost (LCC) of industrial robot production have shown considerable developments, but there remains a lack of methods that allow for the examination of robot substitution. Taking inspiration from the symmetry philosophy in manufacturing systems engineering, this article further establishes a comparative LCC analysis model to compare the LCC of the industrial robot production with traditional production at the same time. This model introduces intangible costs (covering idle loss, efficiency loss and defect loss) to supplement the actual costs and comprehensively uses various methods for cost allocation and variable estimation to conduct total cost and the cost efficiency analysis, together with hierarchical decomposition and dynamic comparison. To demonstrate the model, an investigation of a Chinese automobile manufacturer is provided to compare the LCC of welding robot production with that of manual welding production; methods of case analysis and simulation are combined, and a thorough comparison is done with related existing works to show the validity of this framework. In accordance with this study, a simple template is developed to support the decision-making analysis of the application and cost management of industrial robots. In addition, the case analysis and simulations can provide references for enterprises in emerging markets in relation to robot substitution.
... N times of globalization, demand rises for agility, innovation, and quality. Furthermore, shortened product life cycles and an amplified variety of product models have increased pressure on product manufacturers [1], [2]. In order to keep up with the global competition as such, optimizing product costs throughout a product's life cycle has become a major driver for economic success. ...
... This is extremely helpful to simulate different approaches toward process support (see Background). To stress the argumentation of [10] once more (see Processes Modeling (1) and User Scenario Design (2)) and, thus, enable an evaluation in institutional environments, we designed the clickable UI prototype to integrate with mockups of SAP Product Lifecycle Costing (Figure 9) [35]. This software is a dedicated solution to support early product cost calculation (see Background) a n d i s o n e possible software solution available on the market that could be integrated with our UI prototype [12]. ...
... Besides agility, innovation, and quality, the optimization of costs has become a driver for longlasting economic success. This is especially important for industries such as the process industry or discrete manufacturing industry, as production requires capital-intensive assets and markets are highly competitive; thus, cost effectiveness is a major driver of success [1]. In such an economic environment, it is essential to have a clear overview of product costs. ...
... In addition, current research [34] identifies industrial practice as the most important source for learning about cost reduction projects. For further industry collaboration we consider discrete manufacturing as a research reference due to its 1) distinct product development cycles and 2) demand for cost-effective product development [1]. ...
While theoretical concepts for product-costing methodologies have evolved over the decades, little emphasis has been placed on their integration into modern information systems. During a co-innovation workshop at SAP SE, we initiated our collaborative research with selected large-scale enterprises from the discrete manufacturing industry. Moreover, we conducted interviews with business experts to gain a sophisticated understanding of the cost-optimization process itself. As a result, we present an exemplary optimization process with an emphasis on the specific characteristics of the product development stage. Based upon this example, we identified associated deficits in information system support. No current software fulfills the enterprises' requirements regarding cost optimization in the early stages of a product's life cycle. Thus, the respective processes lack integration in corporate environments. Taking this on, our article compiles detailed problem identification and, moreover, suggests approaches to overcome these hurdles.
... Thus, the asset is not seen from a unique standpoint, but multiple visions exist, each depending on the considered party (Schmidt et al., 2017). Amongst relevant stakeholders, the Original Equipment Manufacturer (OEM), or asset provider, and asset user represents two of the most impactful parties over the asset lifecycle (Roda and Garetti, 2014). ...
The present work considers information and data as a cornerstone for an effective Circular Manufacturing (CM). Focusing on complex industrial assets it also postulates the relevance to develop CM strategies having both the perspective of the Original Equipment Manufacturer, or asset provider, and the asset user. In this scope, a particular emphasis is given on enterprise information systems interoperability as enabler: for CM strategies to be effective, data are required to be exchanged between various enterprise information systems (EIS) hold by the two parties. Therefore, the mapping of data required for each CM strategy along the product/asset lifecycle is performed, and an overview of the EIS interoperability for CM enhancement is discussed, leveraging on ontologies concept.
... The enlargement of the scope towards the AM decision-making is represented by the last block that includes different asset-related decisions. The set of possible decisions to be considered within the scope of AM is large, but generally some classes of decisions could be recognised, from an asset user perspective [24,[30][31][32]: capital investment (evaluation of alternatives/suppliers, maintenance service contract selection, budget planning and cost control) in BoL; operations and maintenance (maintenance planning, operations planning, asset utilisation strategies), reconfiguration decision, and shutdown/turnaround/outage in MoL; reuse or rehabilitation strategy in EoL. ...
Information and data management is nowadays a central issue to support the Asset Management (AM) decision-making process. Manufacturing companies have to take different decisions along the asset lifecycle and at different organisational levels, and, to this end, they require proper information and data management. In the literature, besides the crucial role played by information and data, there is evidence of existing gaps, especially related to information management and integration, and transformation of data into useful information. Thus, a conceptual framework is proposed to guide the definition of a data model to fulfil the previously identified gap. Generally, the framework aims at contributing to the improvement of the integration of information along the AM decision-making process. Specifically, it is intended to be aligned with the AM theory and, in particular, its fundamentals defined in the scientific literature and the ISO 5500x body of standards. Overall, thanks to the improvement of the information management and integration along with the AM decision-making, the expectation is to be capable of achieving more value-oriented decisions for the asset lifecycle.
... Step 7 -TCO calculation. This step allows to evaluate each single scenario, predefined in the previous step, through TCO evaluation [14]. In this step, the CBS cost items are estimated (dependent/independent on the system technical performances) and cost flows discounted, quantifying the net present value for each scenario. ...
This paper proposes a methodology to drive from a strategic point of view the implementation of a predictive maintenance policy within an industrial plant. The methodology integrates the evaluation of system performances, used to identify the critical components, with simulation and cost analysis. The goal is to evaluate predictive maintenance implementation scenarios based on alternative condition monitoring (CM) solutions, under the lenses of Total Cost of Ownership (TCO). This allows guiding the decision on where in the industrial system to install diagnostic solutions for monitoring of asset health, by keeping a systemic and life cycle-oriented perspective. Technical systemic performances are evaluated through Monte Carlo simulation based on the Reliability Block Diagram (RBD) model of the system. To validate the methodology, an application case study focused on a production line of a relevant Italian company in the food sector is presented.
... At the end of the asset lifecycle (EoL), the main decision is related to the selection of decommissioning strategies. For more insights into the asset-related decisions model, refer to [13]. ...
Asset Management (AM) is promising for value creation from assets in the long term. A major concern to this end relates with the capabilities to achieve effective AM decision-making at every organisational level, i.e. operational, tactical, and strategical. Therefore, the goal of this research, grounded on a systematic literature review, is to identify which are the main sources of uncertainty that may influence the achievement of AM system related objectives and, as such, should be taken into consideration in a risk-informed decision-making process. Taking the manufacturing sector as a reference, the risk sources addressed by the extant literature are identified and mapped against a reference classification scheme. As a result, the research offers a comprehensive framework where risk sources, affecting the AM decision-making process, are systematically mapped. Information management is found to be the main risk source when making asset-related decisions.
... Supporting tools can be adopted by the company to aid the achievement of this objective, such as the LCC/TCO. 27,28 Moreover, given that the three stages of the life cycle of the assets-BOL, MOL and EOL-differ in the scope of decisions, different organizational functions need to collaborate in the AM process, covering all organization's hierarchical levels. 19 System orientation is another essential principle to ensure focusing efforts and resources on the right decisions. ...
The aim of this chapter is to investigate how to embed Asset Management in production companies. A framework is defined based on literature analysis and focus groups findings, in which the fundamentals to guide the integration of Asset Management are systematized. Two dimensions are identified—the asset life cycle and the hierarchical level of the asset-control activities—and four founding principles—life cycle, system, risk and asset-centric orientation—as levers to integrate Asset Management within an industrial organization. An empirical investigation is then developed through multiple case-study involving eight production companies in Italy, with the purpose to map the elements of the framework against the real mechanisms in the industrial practices. This allows testing the relevance of the framework itself and demonstrating its potential as a support for companies to implement gap analysis on AM practices. Empirical evidence on current practices of AM in production companies is contextually unveiled.
... This confirms the relevance of TCO for supporting asset-related decision-making at different stages of the asset lifecycle. Indeed, it extends what was already emphasized in a previous review by Roda and Garetti (2014), precursor of the present work. ...
The core concept of this chapter is the total cost of ownership (TCO) of industrial asset and its relevance in supporting decision making, if properly evaluated through the analysis of the technical performances of the asset. The chapter is based on a framework that systematizes benefits and potential applications of TCO for different kind of stakeholders at different stages of the life cycle of the asset supporting different kind of decisions. The aim is to present an experimental case study that has been implemented in order to show the empirical evidence of what is in the framework by focusing on one of the primary companies in the chemical industry in Italy. The application proposes a modeling approach for trying to overcome one main gap that still subsists when referring to TCO models that is that most of the existing ones lack of the integration of technical performances evaluations into the cost models or are based on very limiting hypothesis. In this chapter a comprehensive methodology for the evaluation of Total Cost of Ownership of industrial assets that has being developed within a research activity carried out at the Department of Management, Economics and Industrial Engineering of Politecnico di Milano is presented.
... This confirms the relevance of TCO for supporting asset-related decision-making at different stages of the asset lifecycle. Indeed, it extends what was already emphasized in a previous review by Roda and Garetti (2014), precursor of the present work. ...
This paper proposes a methodology to build a Total Cost of Ownership (TCO) model aimed to support decision-making for manufacturing asset lifecycle management. Existing challenges for TCO adoption in industry are identified through literature review and through an explorative multiple case study involving eight manufacturing companies. Based on it, a general methodology is proposed for building a novel asset-centric performance-driven TCO model. The methodology is based on an integrated modelling approach that puts together technical performance analysis and economic analysis, enabling the asset users linking their knowledge about asset performance with offers specifications by the asset providers. In this way, the TCO model becomes a decision-making tool for the asset users that can also guide the relationship with providers. An application case within a chemical production company is described, showing how challenges are addressed through the proposed methodology, within a real context.
... Optimization of the total cost of ownership (TCO) has gained a lot of attention during the last decade in scientific and industrial research [1], [2]. Many original equipment manufacturers (OEMs) realize that increasing the energy efficiency of their drive trains offers the greatest leverage in reducing the TCO [3]. ...
... Supporting tools can be adopted by the company to aid the achievement of this objective, such as the LCC/TCO. 27,28 Moreover, given that the three stages of the life cycle of the assets-BOL, MOL and EOL-differ in the scope of decisions, different organizational functions need to collaborate in the AM process, covering all organization's hierarchical levels. 19 System orientation is another essential principle to ensure focusing efforts and resources on the right decisions. ...
The aim of this article is to investigate how to embed asset management in production companies. A framework is defined based on literature analysis and focus groups findings, in which the fundamentals to guide the integration of asset management are systematized. Two dimensions are identified—the asset life cycle and the hierarchical level of the asset-control activities—and four founding principles—life cycle, system, risk and asset-centric orientation—as levers to integrate asset management within an industrial organization. An empirical investigation is then developed through multiple case study involving eight production companies in Italy, with the purpose to map the elements of the framework against the real mechanisms in the industrial practices. This allows testing the relevance of the framework itself and demonstrating its potential as a support for companies to implement gap analysis on asset management practices. Empirical evidence on current practices of asset management in production companies is contextually unveiled.
... In times of globalization, demand rises for agility, innovation, and quality. Furthermore, shortened product life cycles and grown variety of product models have increased pressure on product manufacturers and their product portfolios [1]. In order to keep up with the global competition as such, optimizing costs throughout a product's life cycle has become a major driver for long-lasting economic success. ...
In industry, product costs must be optimized to ensure long-lasting economic success. Cost optimization should already be performed during product development, in order to leverage its potential. Previous research has shown that information system support is greatly needed within early product cost optimization. Taking this on, we conducted interviews among discrete manufacturing industry experts, seeking to identify implementation challenges and, moreover, to develop a requirements model to overcome current challenges. To evaluate research results, we joined a co-innovation workshop at SAP SE, during which business domain experts from different industries successfully evaluated our approach. In summary, the concept introduces a promising solution to improve information system support during early product cost optimization.
... The adoption of life cycle orientation in the decision-making processes means that the AM process should incorporate long-term objectives and performances to drive decision making. Supporting tools can be adopted by the company to aid the achievement of this objective, such as the LCC (life cycle cost) / TCO (total cost of ownership) (El-Akruti et al. 2015; Roda & Garetti 2014). Moreover, given that the three phases of the life cycle of the assets are different, different organizational functions need to collaborate in the AM process through multi-disciplinary approach, covering all organization's hierarchical levels (El-Akruti & Dwight 2013). ...
The aim of this paper is to investigate Asset Management (AM) implementation as a business process within production systems to contribute to operational excellence. The main fundamentals to be considered to properly implement AM within production companies according to the existing literature and standards are identified and they are: two dimensions - i.e., the asset life cycle (Beginning of Life, Middle of Life, End of Life phases) and the hierarchical level of the asset-control activities (strategic level, tactical level, operational level) - and four funding principles - i.e., life cycle orientation, system orientation, risk orientation and asset-centric orientation. An empirical investigation is then developed through multiple case-study involving eight production companies in Italy, in order to assess the level of orientation towards those funding principles within production companies as it is nowadays, in order to identify existing gaps and areas for improvements.
... This confirms the relevance of TCO for supporting asset-related decision-making at different stages of the asset lifecycle. Indeed, it extends what was already emphasized in a previous review by Roda and Garetti (2014), precursor of the present work. ...
The core concept of this paper is total cost of ownership (TCO) of industrial asset and its relevance in supporting decision making if properly evaluated through the analysis of the technical performances of the asset. The paper is based on a framework that systematizes benefits and potential applications of TCO for different kind of stakeholders at different stages of the life cycle of the asset, supporting different kind of decisions. The aim is to present an experimental case study that has been implemented in order to show the empirical evidence of what is in the framework by focusing on one of the primary companies in the chemical industry in Italy. The application proposes a modeling approach for trying to overcome one main gap that still subsists when referring to TCO models that is that most of the existing ones lack of the integration of technical performances evaluations into the cost models or are based on very limiting hypothesis. In this paper a comprehensive methodology for the evaluation of Total Cost of Ownership of industrial assets that has being developed within a research activity carried out at the Department of Management, Economics and Industrial Engineering of Politecnico di Milano is presented.
Abstract:
This paper aims to explore different aspects related with the failure costs (non reliability costs) within the life cycle cost analysis (LCCA) of a production asset. Life cycle costing is a well-established method used to evaluate alternative as-set options. This methodology takes into account all costs arising during the life cycle of the asset. These costs can be classified as the ‘capital expenditure’ (CAPEX) incurred when the asset is purchased and the ‘operating expenditure’ (OPEX) incurred throughout the asset’s life. In this paper we explore different aspects related with the “failure costs” within the life cycle cost analysis, and we describe the most important aspects of the stochastic model called: Non-homogeneous Poisson Process (NHPP). This model will be used to estimate the frequency failures and the impact that could cause the diverse failures in the total costs of a production asset. The paper also contains a case study in oil in-dustry where we applied the above mentioned concepts. Finally, the model presented provides maintenance managers with a decision tool that optimizes the life cycle cost analysis of an asset and will increase the efficiency of the deci-sion-making process related with the control of failures.
Keywords: Asset; Failures; Life Cycle Cost Analysis (LCCA); Non-homogeneous Poisson Process (NHPP); Mainte-nance; Reliability Models; Repairable Systems
At the heart of pricing and selling in the twenty-first century is the ability to price based on created value. In this context, total cost of ownership (TCO) plays an important role. Historically, both academics and practitioners have included exclusively elements related to cost reductions in TCO calculations. In this article, we point toward emerging practices of including not only cost elements, but also all differentiating elements that contribute to customer value in TCO calculations.
This paper proposes a generic asset management framework that integrates enterprise decisions for optimising maintenance investment decisions. Optimisation involves finding the best results for an objective with given restraints and relationships. Three business decision dimensions are used-the annualised costs to the enterprise related to maintenance-namely loss of output cost, resources cost and risk cost. The objective is to reduce costs including those due to risks to the minimum. This paper addresses the relationship between these business decision dimensions within the proposed framework and implements the value per unit time approach for optimisation to occur in an integrated fashion.
Purpose
– Asset management is often one of the last options to maximise cost savings in a competitive global economy due to its intrinsic complexity, especially in many developing countries. Asset management in the process industry must consider the commissioning, operational and end‐of‐life phases of physical assets when commencing a design and implementation project. However, current asset management models show inefficiencies in terms of addressing life cycle costs comprehensively, as well as other aspects of sustainable development. An asset life cycle management (ALCM) model is subsequently proposed for assets in the process industry, which integrates the concepts of generic project management frameworks and systems engineering with operational reliability in order to address these inefficiencies.
Design/methodology/approach
– Experiences within a large petrochemical company in South Africa are used as a case study to demonstrate and discuss the different components of the proposed ALCM model.
Findings
– Operational reliability and systems engineering are the means to achieve optimum value from physical assets over a facility's lifetime. Thereby, activities are identified that should be completed during each stage of the project life cycle. The application of performance measurements for the operation and support stages is proposed to influence decision making in the process industry.
Originality/value
– Specific issues pertaining to the ALCM model are highlighted to ensure optimal practicality and incorporation of the model with other management practices in the process industry.
The objective of modern assembly processes is to produce high-quality and low-cost products. Understanding manufacturing costs in the system design phase is the first step to increasing profits. Throughput, utilization, and cycle time continue to be emphasized as key performance indicators for the planning of new assembly systems, but the cost issues need to be analysed as well. The authors are developing a novel analysis methodology that integrates component-based simulation, Overall Equipment Efficiency with Cost of Ownership, and other analysis methods to improve the design of flexible, modular reconfigurable assembly systems. The development of the Total Cost of Ownership (TCO) analysis tool is based on selected industrial standards and the authors’ own experience of assembly system design and simulation. The TCO method is useful in system-supplier and end-user communication, and helps in trade-off analyses of system concepts. A fictitious case study illustrates the use of the TCO method.
Effective through-life management of physical (engineering) assets is essential for any asset-intensive organisation to reach and maintain sustainable levels of growth and value creation. The asset lifecycle starts when the organisation decides to acquire (purchase/lease) an asset to deliver products/service to meet the requirements of the market. Currently, these decisions are made commonly from a price perspective, and increasingly from a through-life cost perspective. However, frequently changing and highly uncertain market requirements can jeopardize the profitability of any organisation whose economic results strongly rely on the effective and efficient utilization of physical assets, when the capability installed in these assets is not matching, over time, the evolution of the market requirements. In such an environment, it is essential to ensure not only that the initial configuration would meet the current requirements, but to be able to reconfigure the assets as market requirements evolve over time. However, this need for reconfiguration and its impact on through-life costing is not accounted for today. This paper takes a first step towards addressing this problem, and presents a modelling approach for incorporating reconfiguration issues in making optimised asset acquisition decisions.
One main challenge in the physical asset management field is to improve the quantification process of costs to evaluate the total cost of a production system throughout its lifecycle (i.e. the Total Cost of Ownership (TCO)). This paper focuses on one main identified gap in literature: most of the currently proposed models neglect the performance of the system, and this brings significant limitations. In fact, the crucial point for the applicability of a TCO model in supporting asset management is that the evaluation criteria for the costs elements definition should encompass not only all incurring cost elements along the asset life cycle but also system performance characteristics like availability on which many of the costs depend. The paper analyses the state of art of the approaches that have been developed adopting ex-ante estimation solutions aiming at predicting total costs through the estimated behavior of asset over the life cycle. After the review the industrial relevance of TCO is discussed considering the perspective of different industries and by identifying the main stakeholders within those industries and the benefits they can rely on having a reliable TCO model.
Collecting data on manufacturing performance and making the results known to those involved could support efforts to improve manufacturing processes. This article describes the conditions for and development of manufacturing cost software developed for analysing connections between manufacturing performance parameters and economic parameters. The conditions for the software were investigated in two pre-studies. The first found that there are commercial software products for manufacturing data collection that support the collection of the data needed for the applied model. The second study demonstrated that the manufacturing companies participating in the second study were largely able to collect the needed data. The developed software, preliminary in character and needing further development, provides information on how the manufacturing performance of a company affects its manufacturing costs. It takes account of six categories of manufacturing cost. A what-if section is included, making it possible to alter the values of various parameters that affect costs in order to analyse how the part cost of a certain component changes with the use of new parameter values compared with historic values.
Abstract Inrecent times the growing,global competition inside the manufacturing industry,is forcing the production systems suppliers to estimate and optimize the overall system Life Cycle Cost, with reference to performance, safety, reliability, maintainability. The production ,system ,supplier must ,dominate ,the ,whole ,process ,from ,concept ,to dismission ,(or conversion). Critical decisions regarding predesign and/or simultaneous,engineering phases,must be taken with particular care, in order to satisfy at best the customer needs. In the present paper a LCC framework,defined by Sintesi SCpA for an automotive supplier is presented. Keywords Life Cycle Cost Model, Life Cycle Cost Software Architecture, Life Cycle CostAutomotive Case Study
Customers of industrial system/machines are becoming increasingly focused on life cycle performance of products for their purchase decisions. Manufacturers of such type of products, for example machine tools, are experiencing increased pressure from customers to deliver customised products with documented reliability, maintainability, maintenance and support characteristics and also with minimum environmental impacts. In this article, first the problem has been explored in the context of Indian machine tool industry and also from literature perspective. Some of the important issues are listed and research steps are identified to address these issues.
In an attempt to improve the design of products and reduce design changes, cost, and time to market, concurrent engineering or life cycle engineering has emerged as an effective approach to addressing these issues in today's competitive global market. As over 70% of the total life cycle cost of a product is committed at the early design stage, designers are in a position to substantially reduce the life cycle cost of the products they design, by giving due consideration to life cycle cost implications of their design decisions. Increasing recognition of cost competition has spurred the development of methodologies such as design for manufacturability, design for assembly (DFA), design for producibility, design for maintainability and design for quality, in the design for 'X' realm. Although these methodologies have for the most part proven successful in reducing cost, the design evaluation criterion in most of these methodologies is not cost. Therefore methodologies and tools are needed to directly pro
Purpose
Despite existing life cycle costing (LCC) method descriptions and practicable suggestions for conducting LCC analyses, no systematic analyses on actual implementations of LCC methods exist. This paper aims to review reports on LCC applications to provide an overview of LCC uses and implementation feasibility.
Design/methodology/approach
A review of LCC cases reported in academic and practitioner literature. Case reports were compared against one another and against the defining articles in the field.
Findings
Most of the reported LCC applications were far from ideal. Compared to the methods suggested in the literature many of the case study applications: covered fewer parts of the whole life cycle, estimated the costs on a lower level of detail, used cost estimation methods based on expert opinion rather than statistical methods, and were content with deterministic estimates of life cycle costs instead of using sensitivity analyses.
Research limitations/implications
This review is limited to reported LCC applications only. Further research is encouraged in the form of a field‐based multiple‐case study to reveal context‐specific dimensions of LCC analysis and implementation challenges in more detail.
Practical implications
This review highlights the difficulty of conducting a reliable LCC analysis, and points out typical problems that should be carefully considered before drawing conclusions from the LCC analysis.
Originality/value
First systematic analysis of LCC applications that gives directions for further research on the LCC concept.
The general global problems in the capital intensive industry seem to be over-capacity and low returns on investment. The means to increase returns on investment are to decrease the operating costs or to increase the turnover of capital. From the physical assets’ point of view, these requirements mean a need for dynamic and continual life cycle management, optimal capacity development, higher overall equipment effectiveness, higher reliability and flexibility of physical assets, and lower maintenance costs of production equipment.
In order to develop methods, such as dynamic life cycle management, optimal capacity development, OEE development etc., to manage the above mentioned problems a general asset management framework is needed. Theframework should be based on the business objectives of the firm and on analysing and mO’Delling various businesses and business environments from the standpoint of the physical assets taking into account technological characteristics, economic structure and uncertainty in the industrial sector in question. In this paper, a methodology to build an asset management framework and a description how it results in asset strategy has been depicted and demonstrated.
Especially in the last two decades of an increasingly-competitive business environment, dwindling resources and an ever-increasing need to obtain value for money in all areas of corporate activity, it has become essential that all available resources be used optimally (Griffith, J. W. and Keely, B. J., Cost Engineering, 1978, September/October, 165–168). Physical assets form the basic infrastructure of all businesses and their effective management is essential to overall success. It has thus become essential to plan and monitor assets throughout their entire life cycle, from the development/procurement stage through to eventual disposal. Life cycle costing∗ is concerned with optimising value for money in the ownership of physical assets by taking into consideration all the cost factors relating to the asset during its operational life. Optimising the trade-off between those cost factors will give the minimum life cycle cost of the asset. This process involves estimation of costs on a whole life basis before making a choice to purchase an asset from the various alternatives available. Life cycle cost of an asset can, very often, be many times the initial purchase or investment cost (Hart, J. M. S., Tetrotechnology Handbook, p. 22, HMSO, London, 1978; Hysom, J. L., Journal of Property Management, 1979, 44, 332–337). It is important that management should realise the source and magnitude of lifetime costs so that effective action can subsequently be taken to control them. This approach to decision making encourages a long-term outlook to the investment decision-making process rather than attempting to save money in the short term by buying assets simply with lower initial acquisition cost. It is suggested project managers should familiarise themselves with what the approach involves, to better appreciate how they might then contribute to the enhanced quality decision making which it makes possible.
Life cycle cost is an essential approach to decide on alter- native rehabilitation strategies for infrastructure systems. Monte Carlo simulation approach is used to develop a sto- chastic life cycle cost (SLCC) model and methodology in order to compare different rehabilitation scena- rios/alternatives for infrastructures, such as water mains. The presented research in this paper identifies several re- habilitation methods for water mains, which are classified into three main categories: repair, renovation, and re- placement. The developed model helps academics and practitioners (e.g. municipal engineers) to predict the suit- able new installation and/or rehabilitation programs as well as their corresponding costs, thereby, to avoid any unplea- sant surprises.
The objective of this article is to present a methodology based on reliability and maintainability (R & M) parameters
for effective implementation of life cycle costing in design and procurement of repairable systems. For this purpose, a
number of life cycle cost models developed over the years have been reviewed, the important life cycle stages for
repairable systems are identified and a generalised model for life cycle cost analysis is first proposed. The
mathematical equations have been formulated for the life cycle stages, such as acquisition, installation and
commissioning, operation, maintenance and repair and disposal. The focus is mainly on modelling the maintenance
and repair costs, which are the major elements of repairable system life cycle cost. To model maintenance and repair
costs, the stochastic point process approach is employed. The lifetime of repairable system is modelled using a two
parameter Weibull distribution. The expected number of failures are estimated based on the assumption that the
number of replacements of the components in an interval (0, t) follow renewal process (RP) in the first case and
minimal repair process in the second case. Based on the expected number of failures, the lifetime maintenance and
repair costs are estimated for the RP and the minimal repair process. A methodology to decide whether a renewal
approach or minimal repair approach should be planned for a particular component is also presented. The proposed
technique is then illustrated through its application to a typical repairable system, namely an industrial pump and
the results obtained are presented along with a review for future work. The proposed model is believed to be a simple
way for system designers to estimate and compare the life cycle cost of their different design alternatives at system
design stage using system R & M parameters.
A physical asset is an entity that is capable of creating, sustaining or destroying value at any stage in its life cycle. Physical asset management is about ensuring that the value profile, as defined by all stakeholders, is enhanced in a sustainable manner throughout the asset's life. This involves the synergistic integration of a wide range of disciplines and processes covering the life-cycle stages of creating, establishing, exploiting and divesting a physical asset in a balanced manner to satisfy the continuum of constraints imposed by business strategy, economy, ergonomics, technical and operational integrity, and regulatory compliance. Innovative approaches that optimise the balance of these constraints are vital during each stage, and also throughout the life of a physical asset. The ramifications for applying such innovative tendencies are a paradigm shift from the conventional cost doctrine typical in maintenance or terotechnology.
Asset Management – an anatomy
- Iam