Imperfect economic production quantity models under predictive maintenance and reworking

Predictive Maintenance and Intelligent Sensors in Smart Factory: Review

“…Tsao et al [116] This study incorporates Industry 4.0, which considers predictive maintenance, into the imperfect production systems into economic production quantity (EPQ) models.…”

“…Method Data Source Al-Jlibawi et al [107] simulation DCS (distributed control systems), PLC, or SCADA in refinery Barbieri et al [99] case study Alternating current (AC) motor (machinery), Pronistia dataset Bekar et al [108] case study Machine motor Farooq et al [38] case study SCADA in spinning factory, spinning frame JWF1562 Goodall et al [92] simulation RFID in remanufacturing facility Chien and Chen [109] case study health status of plasma enhanced chemical vapor deposition (PECVD) chamber tool in TFT(thin film transistor) and LCD (liquid crystal display) company Kiangala and Wang [94] experiment SCADA, conveyor motors Kozlowski et al [110] case study CNC cutter machine sensors for milling of thin-walled aircraft engine components Kumar et al [102] case study CNC machine sensors Lao et al [111] simulation chemical product concentration and temperature profiles Li et al [96] experiment test data from IoT devices and detectors Lin et al [103] experiment test data from IoT in smart factory Musselman and Djurdjanovic [104] experiment automated storage/retrieval systems (belt-driven material handling device) in semiconductor industry Park et al [112] experiment servo motor testing data in smart factory Peng et al [113] experiment NI-PXI (PCI extensions for instrumentation) and NI-Compact data acquisition from production lines in China Steel Corporation Peng and Tsan [98] experiment production line machines Sadiki et al [105] case study industrial machine behaviour Shan et al [114] simulation welding robot in automotive production line Tarashioon et al [115] experiment LED (light-emitting diode) lighting system technologies Tsao et al [116] simulation production system and production lines Uhlmann et al [117] experiment ball and screw monitoring of machine tools Villalobos et al [118] case study melting and extruder machines in plastic bottles production plant (Capital Equipment Manufacturer) Vlasov et al [119] case study the supporting bearing of electric machines (AC motors)…”

“…Sensor Type Sensor Description Al-Jlibawi et al [107] virtual software sensor Barbieri et al [99] vibration B&R X20CM4800X, Beckhoff EL3632 Bekar et al [108] temperature, vibration not available Farooq et al [38] speed, vibration not available Goodall et al [92] position tracking RFID for traceability [114] movement not available Tarashioon et al [115] light, temperature LED sensors architecture Tsao et al [116] not available not available Uhlmann et al [117] vibration, temperature Micro-Electro-Mechanical System (MEMS) of vibration sensors (LIS3DH) Villalobos et al [118] temperature, pressure, speed not available Vlasov et al [119] vibration vibration sensors network Yan et al [120] multiple (vibration, optical, acoustical, power)…”

Production-Inventory System for Deteriorating Items with Machine Breakdown, Inspection, and Partial Backordering

“…Chiu et al [24] extended the model and considered a multi-shipment policy. Tsao et al [25] incorporated the Industry 4.0 concept to support predictive maintenance.…”

A two-stage integrating optimization of production scheduling, maintenance and quality

“…The paper adopted the quality control policy that conditions monitored at the end of the production run and the quality information obtained during the production run. Tsao et al 22 developed an imperfect EPQ model considering predictive maintenance and reworking of defective products. The objective was to determine the optimal predictive maintenance effort and production runtime and minimize the total expected cost.…”