Industry 4.0 digital transformation through fruiSCE^® MES

Manage and handle production orders in all manufacturing environments with proper inventory management, operational reporting, labour and machine accountability, and costing via automated data flow.

Carry out reliable work centre operations, including all material movements, operational time stamp reporting, safety, automatic machine data flow using OPC UA, breakdowns, setup and run times, labor and machine time stamps.

Using live data streaming from the machine (OPC UA protocol), keep an eye on production and machine process effectiveness and take appropriate action if any data points cross the upper and lower specification limitations.

By issuing job orders, assigning resources like supplies and technicians, and receiving summary information regularly throughout the day, you may maintain machinery and equipment through preventative maintenance and ad hoc maintenance.

Assigning tasks to the workers and keeping track of their attendance (leaves, vacations, time-in and time-out stamps, absenteeism) will help you gauge how well they are performing and make your workplace a better place to work.

Increase overall productivity by taking proactive steps to identify machine defects, perform early diagnostics, and replace worn out parts. You should also perform a lead time performance analysis and receive regular information on OEE and SPC performance.

Conduct operations costing by capturing data manually or automatically for machine costs, labour expenses, maintenance costs, and overhead costs, and generating operations costs per unit of product to increase profitability.

AI/ML-enabled alerts or notifications are issued when a production process is affected by any malfunction in a machine or a production line, allowing the required action to be performed to increase manufacturing's safety and productivity.

Manufacturing is given a competitive edge and supply chain safety is increased thanks to the traceability of raw materials, work in progress, and final goods throughout all of the stages of the supply chain.

Using sample and inspection management, quality combinations, and test result analysis, manage the quality and laboratory operations for raw materials, work in progress, finished goods, and procurement, manufacturing, and sales processes.

Identifies the primary inherent risks that exist within the production area, takes into account any processes and procedures used by production planning to regulate the processes using enterprise risk management techniques, and mitigates risks.

Facilitate supply chain automation, integrations, and links to a data lake. From there, connect to specific applications like Process Mining, AI, Analytics, Streaming, and send input to other applications like MES, ERP, etc. to get a competitive edge with data.

Data is provided for conducting process improvement efforts including Lean Six Sigma, TPM, 5S, Kanban, TQM, paperless shopfloors, regulatory compliance, continuous improvement, visibility, OEE, SPC, and AI/ML. Data integration will be seamless in firms that are data ready.

To achieve excellence in manufacturing operations, define OEE, manage it by collecting data from the processing of production orders and automations, and compute OEE at the line, plant, and global levels.

Generate energy consumption plans by production line, production plant with standard consumption requirements and record actual energy consumptions through energy meters automatically and reduce the overall cost of energy consumption.