Process Mining for Construction & Manufacturing

Companies in the construction and manufacturing industry are under great pressure to increase productivity. Machines must be optimally utilized, material flows must function smoothly and production processes must take place with as little downtime as possible. Ensuring efficient production processes is becoming an increasing challenge: material flows are becoming more and more complicated due to reduced production depths, a growing number of variants and increasing globalization.

The Internet of Things (IoT) offers promising solutions to the challenges facing the construction industry. Using networked sensors, the technology makes it possible to monitor machine statuses in real time and detect potential failures at an early stage. Despite the potential, the targeted use of IoT is currently still difficult: the large number of different systems, interfaces and data sources leads to insufficient integration of the available information. The data remains isolated, which makes it difficult to precisely control processes.

This is where Process Mining offers an innovative solution for the construction industry. The method makes it possible to combine IoT data with process analyses, enabling companies to identify process inefficiencies in real time. While the IoT provides the necessary data basis for the construction industry by continuously monitoring machines, materials and processes, Process Mining ensures the systematic analysis and visualization of process sequences. The insights gained enable companies to reduce costs in the long term and thus increase their competitiveness.

The construction and manufacturing industry is characterized by a variety of inefficiencies. Uncoordinated machine utilization repeatedly leads to idle times, while unplanned maintenance and repairs cause production interruptions. Systems that are not optimally utilized are also a common problem. The result: unused capacity and inefficient workflows, which can result in considerable additional costs.

The integration of IoT sensors in Process Mining for the construction industry counteracts this and paves the way for data-driven lean construction management and lean manufacturing. Processes are standardized and production sequences optimized, which reduces waste to a minimum. This is achieved through an innovative combination of machine learning and Process Mining: while IoT sensors continuously record machine data, material flows and environmental parameters, Process Mining transforms this data into meaningful process models using AI-supported algorithms. Modern Process Mining tools have a degree of automation of 80% when it comes to process recognition. This enables companies to efficiently identify process variants and derive best practices. The intelligent integration of domain knowledge into the analysis algorithms provides industry-specific insights and a precise assessment of process quality. Self-learning algorithms analyze the relationships between different process steps and develop predictive models for potential bottlenecks, which prevent failures and simplify scheduling in the construction industry.

Digitalization offers a wide range of opportunities on the construction site and in the manufacturing industry. By combining Process Mining with IoT, companies can consistently implement principles such as lean construction and lean manufacturing and thus leverage untapped potential.