# Indoor Positioning Systems Can Revolutionise Digital Lean
## 1 Introduction  
Internal Positioning Systems provide the possibility of full traceability of manufacturing processes [1]. The main research innovation of this work is to highlight that data provided by IPS systems can be transformed into information that is valuable for Lean-based process improvement. Lean management (LM) is a well-known concept that is widely accepted in manufacturing industries due to its effectiveness in cutting waste and improving operation performance [2; 3; 4; 5]. The tools of Industry 4.0 that advance LM to the next level include simulation and optimization [6; 7], process mining [8; 9; 10], data mining [11; 12; 13; 14], data analytics [15; 16], big data analysis [17; 18], digital twins [19; 20; 21; 22], machine learning [23; 24], virtual reality [25; 26; 27; 28] and cyber-physical systems (CPSs) [17; 29; 30; 31]. An integrative model for LM and Industry 4.0 was studied in [32], which resulted in a flexible and reconfigurable manufacturing system. This brand-new generation was labelled Lean 4.0, with the promise of a different perspective of designing, operating, monitoring and optimizing manufacturing systems [33]. Lean 4.0 follows LM principles as it is built upon a strong foundation of communication and connectivity between equipment and personnel, which allows the key performance indicators (KPIs) to be automatically collected, analysed and modified according to LM measures. Recently, the Lean Industry 4.0 concept has been introduced to surpass the production context within enterprises and to cover the extended supply chain and the logistics network [34]. The tracking of flexible and configurable production systems is not as straightforward as in a simple conveyor, which provides difficulties in controlling internal inventories. The potential of digital lean is unlocked by the integration of operational technology (OT) and information technology (IT) as IT tools can improve the real-time visibility of the value stream. One of the most promising IT elements that can support Lean 4.0, is the Indoor Positioning System (IPS) [35]. This work aims to present how positional data can enrich the toolkit of Lean 4.0-based continuous development of flexible manufacturing systems. The primary function of indoor positioning is similar to GPS, track on a map a tagged mobile unit that can be an asset or person [36]. A typical IPS is an indoor wireless positioning technology [37] that works with radio-frequency, optical, or acoustic tags and chips [38]. The IPS tags are always-active and continuously broadcast signals to beacons [37]. Tags and fixed reference points can be transmitters, receivers, or both, resulting in numerous possible technology combinations [39; 40]. IPS can identify objects' location in a closed structure, thus widely applied in an office building, hospitals, facilities, and warehouses [41]. Compared with other technology including RFID and bar-code scanner, IPS can exclude human error and systematic flexibility, and is robust to any layout change. Due to its intrinsic appropriateness for monitoring logistics units within a manufacturing facility--from items up to packages, transport units, and pallets--IPS has been widely applied in many aspects such as cycle time optimization [42], monitoring production line activities [43], logistics management [44], pallet management [45], safety management [46], and human resource monitoring [47]. This paper aims to develop a detailed guideline about how the information provided by IPS can be utilised in lean management. The proposed method is embedded into the concept of continuous development. The structured DMAIC (Define-Measure-Analyze-Improve-Control) approach utilised in Six Sigma methodology also follows the concept of the Plan-Do-Check-Act (PDCA) cycle [48], which has been proven effective in reducing non-value-added activities in the supply chains and assembly lines [49]. Value Stream Mapping (VSM) is the standard tool for recording processes and identifying waste.