The creation of IT solutions for Industry 4.0 is a rapidly growing field, as businesses seek to take advantage of the latest advancements in technology to improve their operations and increase efficiency. At the heart of Industry 4.0 is the integration of the Internet of Things (IoT), big data, and artificial intelligence (AI) to drive digital transformation in manufacturing and other industries.
When creating IT solutions for Industry 4.0, it is important to start by identifying the specific business objectives that need to be addressed. This could include streamlining production processes, improving supply chain management, or increasing operational efficiency.
Once the objectives have been defined, the design and development process can begin. This includes selecting the right hardware and software components, integrating existing systems and data, and programming the AI algorithms and rules that will drive the solution.
In Industry 4.0, real-time data collection and analysis play a critical role in enabling decision-making and process optimization. This requires robust data management systems and secure, scalable cloud infrastructure to store and process large amounts of data.
Testing and optimization are key parts of the development process for Industry 4.0 solutions. This includes verifying that the solution works as intended, testing for scalability and reliability, and performing security and privacy audits to ensure that data and systems are protected.
The final step in the process is deployment and maintenance. This involves installing the solution in the production environment, training users, and providing ongoing support and maintenance to ensure that the solution continues to meet the evolving needs of the business.
The development of IT technology now makes it possible to have constant access to the necessary business software, information and to integrate planning processes at different levels.Factory automation involves creating uniform procedures for production planning, ordering, inventory management, and proposing a simple computer tool to support collaboration.
The main departments of automation include:
- programming of overhead cranes
- programming of automatic feeders
- programming of forklifts
- planning integration
MES software is the connection between the remote I/O layer (PLC layer) and the ERP layer (enterprise resource planning). This is also called "vertical integration." Inteqnion uses a Microsoft SQL database and ISA-88 and ISA-95 standards to build its MES system. Since enterprise resource planning (ERP) systems contain information on inventory and customer demand, and manufacturing execution systems (MES) control how they are built, integrating the two worlds can help increase operational efficiency and enable organizations to be more flexible and responsive to non-standard and changing requirements. Demand changes recorded in ERP systems can be fed into production schedules to ensure that the volume of products produced is closely aligned with demand for leaner and more efficient production. By integrating ERP and manufacturing data to obtain more accurate demand forecasts, companies can reduce inventory, avoiding overproduction
Supply chain managers can track incoming and outgoing inventory with incredible detail, and this visibility enables brands to respond immediately to changes. With ERP and MES integration, manufacturers can reorder from suppliers before inventory falls below a certain level. Better system integration supports more efficient execution of change orders. Manufacturing Execution Systems (MES) help streamline operations on the shop floor by managing and monitoring all work in progress, including providing real-time visibility and enabling tracking of both materials and products throughout their lifecycle, facilitating corrective action for defective products. Integration of MES with ERP systems enables manufacturers to organize work orders and other resource needs.
Embedded and Sensors development for industry
Embedded sensors have helped optimize the performance of production machines, leading to greater efficiency and productivity gains.
Improving operational efficiency: monitoring work with sensors helps reduce employee idle time by optimizing assignments. Sensors used for quality control on assembly lines close the physical-digital loop of production problems in minutes.
Improved asset management: critical equipment is connected and monitored with sensors to proactively respond to potential interruptions.
Real-time inventory tracking: radio-frequency identification (RFID) sensors used for low-cost, contactless identification and tracking of goods can potentially reduce the risk of reduced or lost inventory. Smart sensors for multi-channel sales, such as products and packaging with embedded smart sensors, enable automated ordering and replenishment.
Product design: connected products provide insights into customer behavior and preferences for more responsive product development.
KPIs and Metrics in industry
KPIs or manufacturing metrics are well-defined measurements used to monitor, analyze and optimize manufacturing processes in terms of quantity, quality and various cost aspects. They provide manufacturers with valuable business insights to help them achieve organizational goals created by IT value.
The throughput KPI measures the production capacity of a machine, line or plant; also known as how much they can produce in a certain amount of time.
The cycle time measure can be used to measure the time it takes to produce a complete product, each individual component of a final product, or even to include delivery to the end user.
Demand forecasting - this measure of production is used by companies to estimate the amount of raw materials they will need to meet future customer demand
Inventory turnover - this is a measure of how many times inventory is sold over a specified period of time and helps determine resource efficiency
Production Achievement - this metric of production performance measures production levels over a specified time interval and calculates what percentage of the time the target production level is achieved.
Cash to Cash Cycle Time - this is a time-based production KPI metric. It measures the amount of time that elapses from the initial cash outlay for raw materials, inventory or production facility until the company receives cash from its customers for its products. This KPI is usually measured in days.
Measuring costs will allow you to create low-cost solutions which can translate into big savings
Shift time - Typically in manufacturing, it represents the amount of time lost in switching the production line from one product to another
Clock time is the maximum allowable amount of time that can be spent producing a product while meeting a customer's deadline
Return on assets (ROA) - This ratio assesses how well your company is using its assets (money). It is annual net income divided by total assets (fixed assets + working capital).
Value Stream Management
Value stream management is a lean business practice that helps determine the value of the work and resources involved in rapid development and delivering business software. It also helps streamline the flow of value to the organization while managing and monitoring the software delivery lifecycle from start to finish. By identifying and examining value streams instead of "features and functions" and measuring the success of software delivery, teams can focus more energy and time on what works and move away from what doesn't
Value stream management offers a unique view of the software delivery lifecycle through the lens of customer service to better align with business goals and scale Agile and DevOps transformations.
- See actual delivery time, cycle time and throughput instead of guessing this data based on inconsistent and outdated reports
- Become aware of the actual time it takes to deliver value to the customer , so you can manage expectations and detect areas of inefficiency
- Rely on a single source of truth to see all DevOps pipeline metrics in one place, so everyone on teams has the same information.
- Create more realistic goals , better alignment and smoother communication between business and IT technology
- Establish a comprehensive, accurate baseline from which to build a long-term improvement plan .