A framework for evaluating remote diagnostics investment decisions for semiconductor equipment suppliers

Vardar, Cem; Gel, Esma S.; Fowler, John W.

doi:10.1016/j.ejor.2006.05.020

Cited by 11 publications

(6 citation statements)

References 26 publications

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“…The existing literature on remote technologies has focused on the various technical details (e.g. sensors, data analysis techniques, databases), thus providing case-based evidence (Vardar et al , 2007) and illustrations (Lee, 1998; Levrat et al , 2008), particularly from a technology perspective. Conversely, servitization research has examined the importance of remote technologies in collecting information on an installed base (Johnstone et al , 2009; Ulaga and Reinartz, 2011; Wise and Baumgartner, 1999).…”

Section: Introductionmentioning

confidence: 99%

“…Studies have also emphasized the importance of using remote technologies for preventive and predictive maintenance (Brax and Jonsson, 2009; Huikkola et al , 2016). As a result, prior research linking servitization and IoT has focused on the technical details regarding IoT (Ala-Risku, 2009; Lee, 1998; Levrat et al , 2008; Muller et al , 2008; Vardar et al , 2007) mostly neglecting the strategy perspective (Eloranta and Turunen, 2015; Porter and Heppelmann, 2015). Hence, to capture the capabilities required from the manufacturers, IoT needs a clear model defining its use and value.…”

Section: Introductionmentioning

confidence: 99%

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Modeling manufacturer’s capabilities for the Internet of Things

Hasselblatt

Huikkola

Kohtamäki

et al. 2018

JBIM

113

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Purpose This paper aims to identify a manufacturer’s abilities to develop, build, sell and deliver Internet of Things (IoT) services. Design/methodology/approach This paper is a qualitative comparative case method that uses multiple sources of data, including executive interviews and secondary data, to understand a manufacturer’s IoT capabilities. Findings Five strategic IoT capabilities were identified: digital business model development, scalable solution platform building, value selling, value delivery and business intelligence and measurement. Research limitations/implications The main limitations are related to the qualitative research method applied. The results are applicable mainly to relatively large and global manufacturers. Practical implications Managers responsible for solution business development can apply the developed model to acquire and manage IoT specific resources, processes and capabilities. Originality/value Existing studies have not addressed the IoT-specific resources, processes and capabilities that manufacturers’ possess. This is one of the first studies to conceptualize how these capabilities are used.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling manufacturer’s capabilities for the Internet of Things

Hasselblatt

Huikkola

Kohtamäki

et al. 2018

JBIM

113

View full text Add to dashboard Cite

show abstract

“…Robotis et al (2012) optimized the price and lease time of various equipment, as well as the variety of maintenance and remanufacturing measures were also considered in this model. Vardar et al (2007) proposed a queuing model based on location, capacity analysis, situations and after-sales services. They used optimization and simulation methods for exploring feasible space to solve this problem.…”

Section: Literature Reviewmentioning

confidence: 99%

Simulation and optimization for improving performance of maintenance

Ershadi

Shemirani

2020

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Purpose The purpose of this paper is to design an applied mathematical model to maximize the profits of maintenance activities in manufacturing organizations, also providing an efficient solution method for that. Design/methodology/approach Reviewing published articles in the field of maintenance planning and then trying to model the problem to optimal decision making in this field. Findings Maintenance optimization can be done more appropriately by the accurate use of mathematical programming. Research limitations/implications The existence of probabilistic parameters in this problem leads to hard stochastic programming. Practical implications Designing and organizing maintenance activities will increase productivity. This paper attempts to use mathematical models to optimize this matter. Originality/value This paper highlights the importance of using optimization methods for maintenance planning.

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“…Wang and Christer (2000) have examined a technique for modelling CBM decision making for plant with dual maintenance actions of preventative and replacement. Vardar et al (2007) designed a queuing-location model to assess the adequacy of after-sales service providers through information from remote diagnosis tools. While assuming the consequences of congestion, the model optimises the place, capability, and the service centre category by means of a simulation optimisation based on genetic algorithms.…”

Section: Maintenance Approachesmentioning

confidence: 99%

Assessing asset monitoring levels for maintenance operations

Alabdulkarim

Ball

Tiwari

2015

Journal of Manufacturing Technology Management

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Purpose – Asset management has recently gained significance due to emerging business models such as Product Service Systems where the sale of asset use, rather than the sale of the asset itself, is applied. This leaves the responsibility of the maintenance tasks to fall on the shoulders of the manufacturer/supplier to provide high asset availability. The use of asset monitoring assists in providing high availability but the level of monitoring and maintenance needs to be assessed for cost effectiveness. There is a lack of available tools and understanding of their value in assessing monitoring levels. The paper aims to discuss these issues. Design/methodology/approach – This research aims to develop a dynamic modelling approach using Discrete Event Simulation (DES) to assess such maintenance systems in order to provide a better understanding of the behaviour of complex maintenance operations. Interviews were conducted and literature was analysed to gather modelling requirements. Generic models were created, followed by simulation models, to examine how maintenance operation systems behave regarding different levels of asset monitoring. Findings – This research indicates that DES discerns varying levels of complexity of maintenance operations but that more sophisticated asset monitoring levels will not necessarily result in a higher asset performance. The paper shows that it is possible to assess the impact of monitoring levels as well as make other changes to system operation that may be more or less effective. Practical implications – The proposed tool supports the maintenance operations decision makers to select the appropriate asset monitoring level that suits their operational needs. Originality/value – A novel DES approach was developed to assess asset monitoring levels for maintenance operations. In applying this quantitative approach, it was demonstrated that higher asset monitoring levels do not necessarily result in higher asset availability. The work provides a means of evaluating the constraints in the system that an asset is part of rather than focusing on the asset in isolation.

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A framework for evaluating remote diagnostics investment decisions for semiconductor equipment suppliers

Cited by 11 publications

References 26 publications

Modeling manufacturer’s capabilities for the Internet of Things

Modeling manufacturer’s capabilities for the Internet of Things

Simulation and optimization for improving performance of maintenance

Assessing asset monitoring levels for maintenance operations

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