Digitalization & Industry 4.0
How do some of the leading organizations use Industry 4.0 Concepts? In this post, I will share my insights and experience from advising, steering and being part of digital transformations in organizations around Europe, North America and, Asia.
What is Industry 4.0:
The fourth Industrial revolution includes advancement in automation, internet of things (IoT), cloud computing and cognitive computing. There is a significant change in the way we produce products and services based on digitization. The name of this transformation is called Industry 4.0 and is representing the fourth industrial revolution. As advancements in technology are improving, this digital transformation has started to transform our way of living, working and connecting with each other.
The key aspect is data exchange where cyber-physical systems can communicate and monitor physical processes, cooperate with each other and interact with humans in real-time. In a factory setting, this means that machines will be automated and digitally connected with each other and their human co-workers to become more efficient and productive.
The term “Industry 4.0”
To start with, Industry 4.0 is not a business discipline or a new technology; rather it is best described as a new approach to achieving greater efficiency and productivity.
The term “Industry 4.0” originates from a project done in the high-tech strategy of the German Government. The project promotes computerization of manufacturing. The term has also some historical perspective referring back to the first, second and third industrial revolution.
The first industrial revolution in the 19th century saw the rise of mechanization, water power and steam power which brought factory production. The second industrial revolution spanned from the1850s to World War I introduced mass production, assembly lines and electricity. The third industrial revolution took place from the 1950s to the late 1970s and refers to change to from mechanical and analog technology to digital technology. And the fourth industrial revolution is about the move towards digitization, big data, and data analytics. The figure above shows the four industrial revolutions.
The Three Most Important Things You Need To Know About BUSINESS MODEL in INDUSTRY 4.0
The speed and depth of this industrial revolution are significant compared with the other societal transformation. This means that organizations need to ask some serious questions concerning their operational capabilities and assess the opportunities to create value-added solutions for customers and end-users. How can organizations continue satisfying customer needs and make a profit on it? This is a relevant question and will be disrupted by agile competitors realizing the industry 4.0 potentials.
Industry 4.0 will change what is produced, the way it will be produced and the way it is used. We will look at the three effects to consider when designing new business models:
One development is the concept of mass customization where individual customer requirements need to be met. Customer will be able to design their own specific product – e.g. shoes or clothes. The product development process will be more collaborative, adaptive and transparent. Further on, the life-cycle of a product will be extended to include services to be added together with products and thus create additional value for end-users. These services will enable new pricing models such as Pay per X or Pay as you need. One example of this is car-sharing that can be rent and shared.
With the rapid development of technology, automation in industrial production is inevitable. As robots will get smarter with embedded sensors it is possible to have self-optimizing production facilities. Robot process automation will be able of handling of routine works such as customer service tasks. With driver-less trucks and automated drones, transportation systems will change how we transport and deliver products.
Big data and connected products and services:
With the big amount of data generated in this transformation, it will change problem-solving, decision-making, technology and communications. In problem-solving, machine learning algorithms can be used to find patterns. In decision-making, already forecasting in the supply chain is improved by utilizing data from customers, suppliers, and users. In technology innovation, the use of 3D printing and blockchain technology can enable a new type of products and services. Finally, communications will also be impacted by new technology innovations such as augmented reality and virtual reality. Already, there are several cases in the construction industry where virtual reality technology is used to improve design, safety, and training, and to avoid costly overruns. Imagine video conferences for construction and building inspections by the use of virtual reality where computer-generated experience is taking place within a simulated environment.
3 INDUSTRY 4.0. REAL-WORLD Case Studies
The use of ROBOT PROCESS AUTOMATION to Increase EFFICIENCY
Leading industrial company and service organizations are driving development with robotization and automation. The use of automation spans from Swedish Municipalities to global logistics companies, the aim is to automate repetitive and pre-defined process steps. Robot Process Automation (RPA) software is getting smarter due to increasing computer power and is becoming easier to use and modify. In one global logistics company, process steps such as manual invoicing and ERP data entry were automatized by using RPA software. Business benefits include cost saving, error reduction and, increased volume processed. The main takeaway for me was.
- Start with understanding the input, output, deviations and variations in your process
- Before attempting RPA technology to any process first aim to stabilize the process: Data format should be standardized
- Continuously monitor the process to make sure that the software is executed as designed. One method that can be used is the PDCA/Deming Cycle, see figure below. It is used in business for the control and continuous improvement of processes and products.
Smart Intelligent Devices and Wearable’s to improve safety and quality
The leading industrial manufacturers are using smart intelligent devices and wearable’s to improve productivity, safety and, quality in their manufacturing lines. Smart drones are being used for inspection of the buildings, stock controls in warehouses and to monitor safety conditions in the plants. Other examples include the use of smartwatches in manufacturing lines worn by line operators and the use of Augmented Reality glasses for rapid quality inspection and maintenance. The main learning’s for me was.
- Digitalization tools will not replace the philosophy of respect for people and society, focus on the customer and continuous improvement. Work closely together with those who will be impacted to collect requirements and ideas before attempting implementation of digital tools.
- Start by mapping the flow of your processes and remove unnecessary activities that don’t add value to the customer. The figure above shows an example of an value stream mapping. Before seeking digital solutions, identify the areas for productivity gains by using quantitative and qualitative mapping tools. Measure lead-time, throughput time and see for yourself. Technical people cannot invent digital solution in their remote offices, always GO to GEMBA and interact with to those that are actually performing the activities.
Big Data, Data Analytics and Machine Learning in Supply Chain Management
The term big data is referring to a large volume of data – both structured and unstructured. Data will play a key role in this new transformation as products will be “smarter” embedded with sensors. This means that data can be generated in real-time for gathering and analysis to identify patterns and insights. With the volume of data increasing in 2019 it will be possible in the wider context apply analytics to business data to describe, predict and improve performance. One area of specific interest is machine learning by using mathematical models of sample data to make predictions, learn from the data and identify unknown patterns.
As managing supply chains are getting more complex, data analytics can help to bring new customer insights and increase the visibility of inventory levels and demand. With the help of data analytics tools, it is now possible to collect data from different sources and turn it into useful information. The structural relationship between data, information, knowledge and wisdom is shown in the DIKW pyramid in the figure above. In one real-world example, a team consisting of data scientist worked together with transport and logistics developer to improve delivery routes using big data. The data can be collected from weather services, data from traffic services, customer surveys and, operations data from plants and distributions center. Internal inbound logistics is another area that can be improved by combining data from ERP systems, barcode systems and, claims data to improve picking and shipping. As a result, the aim of many supply chain operations is to become more demand-driven and achieve an E2E segmented supply chain strategy. The main takeaway for me was.
- One pitfall where many organizations fail: They don’t begin by defining the problem they want to solve and don’t ask the right questions linked to business goals.
- Identify the “why”: The aim should be to transform information into actionable knowledge in order to improve business decisions. In many cases, data analytics and machine learning imitative are only resulting in colorful presentations.
- To fully utilize the power of data analytics, the teams working on business problems should be cross-functional. To identify, learn and make decisions from the various sources of data, it is needed to bring together knowledge from different functions within the organization. In this way, it will be possible to combine know-how in statistics, programming and operations.
Computer power and bandwidth, the cost associated with these technologies have become cheaper. This means that firms and governments have reached a point that these technologies can be used with an economic benefit. As a result, we will see changes in business models, how we work and consume goods and interact with each other in a globalized world.
How these changes will look like will be up to us to decide. I am hoping that this can revitalize our economy, bring people closer to each other and create sustainable solutions for everyone
How is your organization using Digitalization and Industry 4.0 concepts and tools? Please, share your comments below.