## 2 Literature Review  
### Data Driven Process Improvement  
Many process improvement models were developed over the years for improving specific aspects in the manufacturing industry, based on the six competitive priorities above-mentioned. Models, such as total quality management (TQM), Lean manufacturing, Six Sigma, and Lean Six Sigma (LSS) are most widely known for process improvement [11]. Lean was a systematic concept introduced by Toyota in the 1950s after World War II; it was labelled as Lean manufacturing in 1990, in a book by [PERSON], [PERSON], and [PERSON] [12]. It was the more common process improvement model adopted by industries for reducing waste and improving processes. Eliminating waste allows reducing process cycle time [13]. Cycle time is defined as the total time taken by the component in the production cycle [14]. Reducing cycle time will increase overall product output and ensure that customer demand is met. Six Sigma was first developed in 1986 by Motorola [15]. It uses statistical means to produce high-quality products by reducing process variation [16]. The aim of Six Sigma is to maintain a defect rate of below 3.4 defective parts per million for a process. This means that 99.99% of the process output will consist of fault-free good parts. Reduction in defective parts will reduce the cost of non-conformance and energy consumption. Two methodologies can be applied in Six Sigma: DMAIC for improving existing process and DMADV for developing a new improved process [12]. [PERSON] and [PERSON] [7] stated that large companies have benefited (i.e., profit increasing) by implementing Six Sigma, which is a tool used by organizations to minimize process variation and eliminate waste. With the implementation of Six Sigma, it is possible to determine the critical factors, the optimal operating levels or tolerances, and other improvement opportunities [7]. Six Sigma was used to reduce electrical defects in a circuit cartridge manufacturing plant [17]. It was also used to improve product dents in forging plants [16]. [PERSON] [18] used Six Sigma to improve the heat treatment process and hardness quality of tools and dies. [PERSON] and [PERSON] [19] decreased the scrap rate in a plastic injection molding plant by using the Six Sigma methodology. IT departments have also benefited from using Six Sigma by reducing customer support issues [20]. [PERSON] and [PERSON] [21] investigated the existing problems in a software industry and proposed the improved engineering process improvement model (using an engineering design process called Design for Six Sigma). A corrugated box manufacturing company reduced 22.7% of its waste by applying the DMAIC Six Sigma framework [22]. Implementation of Six Sigma in automobile industries and thermal power plants have also shown positive outcomes [23,24]. Table 1 summarizes the methodologies described in various research publications on the subject. Lean Six Sigma (LSS) has also been used in equipment maintenance in industries for quality management and process optimization [13,30]. [PERSON] et al. [25] successfully reduced non-value-added activities and delivery time by implementing LSS in the aerospace industry. Lean and Six Sigma were previously used in conjunction because Six Sigma uses statistical means to improve the process and Lean focuses on value stream mapping (VSM) for reducing waste and non-value-added operations [31]. Lean was also used with robotic process automation (RPA) in literature for process improvement, in terms of automation [29]. RPA is defined as a category of software tools that allows repeated or routine actions to be automated using structured data, rules, or logged interactions [32,33]. Therefore, the identification of automation opportunities using RPA is very limited. The Lean strategy helped identify the action to be automated in this study [29].