# Lead time prediction using machine learning algorithms: A case study by a semiconductor manufacturer

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/lead-time-prediction-using-machine-learning-algorithms-a-case-study-by-a/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Lukas Lingitz,Viola Gallina,Fazel Ansari,Dávid Gyulai,András Pfeiffer,Wilfried Sihn,László Monostori |
| Citations | 144 |
| DOI | 10.1016/j.procir.2018.03.148 |
| Fields | Engineering |
| Open Access | true |
| OA Status | diamond |
| OA URL | https://www.sciencedirect.com/science/article/pii/S2212827118303056/pdf |
| OpenAlex ID | https://openalex.org/W2811113727 |
| Type | article |
| Year | 2018 |

## Paper authors

- [Fazel Ansari](https://scholariq.org/researchers/fazel-ansari/)

## Paper journal

- [Procedia CIRP](https://scholariq.org/journals/procedia-cirp/)

## Paper primary topic

- [Scheduling and Optimization Algorithms](https://scholariq.org/topics/scheduling-and-optimization-algorithms/)

## Paper topics

- [Scheduling and Optimization Algorithms](https://scholariq.org/topics/scheduling-and-optimization-algorithms/)
- [Flexible and Reconfigurable Manufacturing Systems](https://scholariq.org/topics/flexible-and-reconfigurable-manufacturing-systems/)
- [Manufacturing Process and Optimization](https://scholariq.org/topics/manufacturing-process-and-optimization/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.