A Web Services-Based Collaborative Planning, Forecasting, and Replenishment (CPFR) Framework for Managing Spare Parts of Semiconductor Equipment

Chen, Mu-Chen; Chen, Kai-Ying; Hsu, Ming-Fu; Yeh, Chun Chang

doi:10.1109/tsm.2009.2028217

Cited by 5 publications

(1 citation statement)

References 8 publications

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“…Collaborative forecasting and planning of spare parts between suppliers and manufacturers can be beneficial. It can improve service levels on the supplier side, thereby allowing manufacturers to decrease spare parts inventory (Chen et al ., 2009). More information on the customer demands within the supplier network helps suppliers assure a certain service level (Branska, 2011).…”

Section: Opportunities For Internal Integration Supported By Data-dri...mentioning

confidence: 99%

Data-driven decision-making in maintenance management and coordination throughout the asset life cycle: an empirical study

Hinrichs,

Prifti,

Schneegass

2023

JQME

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PurposeWith production systems become more digitized, data-driven maintenance decisions can improve the performance of production systems. While manufacturers are introducing predictive maintenance and maintenance reporting to increase maintenance operation efficiency, operational data may also be used to improve maintenance management. Research on the value of data-driven decision support to foster increased internal integration of maintenance with related functions is less explored. This paper explores the potential for further development of solutions for cross-functional responsibilities that maintenance shares with production and logistics through data-driven approaches.Design/methodology/approachFifteen maintenance experts were interviewed in semi-structured interviews. The interview questions were derived based on topics identified through a structured literature analysis of 126 papers.FindingsThe main findings show that data-driven decision-making can support maintenance, asset, production and material planning to coordinate and collaborate on cross-functional responsibilities. While solutions for maintenance planning and scheduling have been explored for various operational conditions, collaborative solutions for maintenance, production and logistics offer the potential for further development. Enablers for data-driven collaboration are the internal synchronization and central definition of goals, harmonization of information systems and information visualization for decision-making.Originality/valueThis paper outlines future research directions for data-driven decision-making in maintenance management as well as the practical requirements for implementation.

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Section: Opportunities For Internal Integration Supported By Data-dri...mentioning

confidence: 99%

Data-driven decision-making in maintenance management and coordination throughout the asset life cycle: an empirical study

Hinrichs,

Prifti,

Schneegass

2023

JQME

View full text Add to dashboard Cite

show abstract

Learning curves in collaborative planning, forecasting, and replenishment (CPFR) information systems: An empirical analysis from a mobile phone manufacturer

Yao

Kohli

Sherer

et al. 2013

J of Ops Management

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a b s t r a c tWhile Collaborative Planning, Forecasting, and Replenishment (CPFR) information systems have been increasingly deployed to improve supply chain operations in a cross section of industries, the extant literature has largely overlooked the learning effects within organizations, thereby resulting in incomplete assessment of their business value. Using an operational-level panel data for nine product lines over 2.5 years, we empirically examine the learning curves in CPFR between Motorola, a mobile phone manufacturer, and one of its U.S.-based national retail partners. We found that the two key components of CPFR, collaborative forecasting (CF) and collaborative replenishment (CR), exhibit distinct learning curves. Forecast accuracy improves immediately following CPFR implementation but the rate of improvement slows over time, whereas inventory levels increase at first and begin decreasing after a period. Further, we found different learning effects in terms of inventory levels when products are later replaced with new form factors. Product replacements have lower inventory levels than their antecedents, at least for lowend products. We discuss important implications for theory and practice at the interface of information systems and operations management.

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An efficient data exchange scheme for semiconductor engineering chain management system

Hung

Wang

et al. 2010

Robotics and Computer-Integrated Manufacturing

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A Web Services-Based Collaborative Planning, Forecasting, and Replenishment (CPFR) Framework for Managing Spare Parts of Semiconductor Equipment

Cited by 5 publications

References 8 publications

Data-driven decision-making in maintenance management and coordination throughout the asset life cycle: an empirical study

Data-driven decision-making in maintenance management and coordination throughout the asset life cycle: an empirical study

Learning curves in collaborative planning, forecasting, and replenishment (CPFR) information systems: An empirical analysis from a mobile phone manufacturer

An efficient data exchange scheme for semiconductor engineering chain management system

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