Cantier MES 4.0

Product configuration defines the characteristics of every product and parts, components and materials that make up the physical dimensions of these products. Also, this module defines the Manufacturing Process or Routes required to build, assemble, and plan to ensure that the finished goods meet the overall product specification in terms of dimensions, functionalities, color schemes, and cosmetic design.

It has the feature to create RFID tags that embed the product configuration of a particular product or part. This will help in the shop floor to broadcast the Product Configuration information to the machines such as Recipe, materials used, tools used, etc. Also this feature enables automated parts placement, assembly and inspection machines switch programs based on the received product information from each unit. This feature is very crucial for SMART Production Facility.

Once the materials, tools and spare parts from the warehouse are withdrawn, several factories have no control over the materials and spare parts lying on the shop floor. They treat them as expenses directly upon withdrawal from the warehouse. This can be addressed and tracked using Shop Floor Inventory that is part of Cantier MES. The Shop-floor Inventory Management records all movements of stock, from receipt, inspection, transfers and issuance in the shop floor. This is with the process of barcoding or RFID integration.

With the help of Factory Planning MRP run, MES calculates the required materials for their upcoming production in their line or site and request the necessary materials from their warehouse for their Kitting activity. At any given time, we can view the details of inventories by site, line, process or even per equipment. Cantier MES enables just-in-time inventory to prevent understocking or overstocking and thus it ensures a lean inventory.

With Barcode/RFID capabilities, we can easily identify the right materials or parts for the issuance or transfer to the shop floor. RFID Readers help tracking of the materials located in the shop floor automatically.

We are in the age of Industry 4.0 and it requires mass customization than just mass production. With this new challenge, manufacturers must respond rapidly and intelligently to the unpredicted changes and to deliver the outputs in a shorter lead time. Cantier Factory Planning & Scheduling is specifically designed to meet the current trend and need in the industry.

Material Requirements Plan(MRP)
MRP breaks down the customer order and/or sales forecast quantity into component material requirements using the latest product, BOM explosion, to compute the gross materials requirement. The current inventory result and the outstanding purchases are considered in order to calculate the next requirements. Based on the suppliers’ acceptable Minimum Order Quantity (MOQ) and delivery lead time, actual part purchase quantity is adjusted, and a Purchase Requisition is created for management approval. In this manner, the system helps you to deliver parts on time while maintaining inventory and Work In Process (WIP) to an optimal level.

Production Scheduling
It generates job orders based on the demand and forecast and provides Earliest start date of each Job order. It also calculates how much work can be produced in a certain period of time, taking into consideration resource constraints (materials, equipment, tools, and people) generates a line loading schedule

Traceability of manufactured products and lineage of data availability are key to certain industries for damage control purposes. This is particularly true for industries such as Semiconductor, Electronics, Automotive, Aerospace, Medical & Surgical, FOOD, and Military & Defense.

WIP Traceability
WIP Traceability enables the manufacturer to track the manufactured products or materials as they flow in the production floor as well as record keeping of the parts source, material certificate, number, batch number, date of manufacturing, inspection date, and etc. This lineage of information will facilitate quick recall of the identified defects and prevent further damages or failures to the overall final product safety which at times, can be life threatening.

WIP Traceability captures the relevant data as part of the lot history including:

• Batches/serial ID of material components used and replaced
• Operator who worked on the lot
• Machine/Tool ID used in the process
• Defect/Rework breakdown
• Adequate data to correlate product quality with process parameters that drive continuous process improvement

Cantier SPC with the intelligence capability collect data real-time, analyzes data based on user defined tests, and helps draw conclusions. Hence manufacturers make data-driven decisions to improve product quality, reduce risk, and to meet compliance requirements. With the machine learning intelligence features, Cantier SPC provides Predictive Quality based on the historical data.

Since the 1920’s, manufacturers of products around the world have seen the need to use applied statistical methods to understand inherent process variation, reduce it and control it.

Statistical Process Control
In today’s complex manufacturing processes, a tremendous amount of data is typically available. Collecting, organizing, analyzing, and presenting data that can be used by decision makers from the operator up to the plant manager, represents a huge challenge for the manufacturer.

On the collection side of the equation, the Cantier SPC can acquire data through IIoT gateway to the metrology equipment and tools. It acquires data inputs from PLCs, Industrial PCs, PC based programs like MS Excel, CSV Files, Text files and other formats.

While on the analysis side of the equation, Cantier QMS can help you sense of the data using several analysis tools. Examples include Frequency Distribution, Control Charts, Run Charts, Pareto Charts, MultiVar Charts, etc.

Cantier Document Control Center (DCC) reduces the paper-based documents. It centralizes all needed documents and makes only the latest revision of each document available to other tools within QMS and other Cantier System modules. Morever, DCC can accept multiple document formats such as, CAD/CAM Files, MS Word, MS Excel, PDF, as well as photo formats, video formats, and others. Examples of the data that can be retained in DCC:

Document Types:

• Raw material and manufacturing specifications
• Customer and internal control plans
• Engineering drawings.
• Standard operating procedures
• Setup checklists
• Equipment maintenance procedures and checklists
• Packaging and labeling instructions etc.

Cantier CMMS (Computerized Maintenance Management System) provides users with a set of tools needed to track, predict and improve equipment performance in the factory. CMMS manages scheduled, unscheduled equipment maintenance and predictive maintenance activities. Predictive maintenance includes Usage based and Condition based maintenance activities from the real-time data being collected from the IIoT Gateway that is connected to PLCs, Industrial PCs, Edge Devices and Sensors. Machine Learning models based on the historical data predicts equipment failures and proactive maintenance incidents. CMMS helps companies monitor and improve Maintenance KPIs such as MTBA, MTBF, MTTR, OEE and thereby increasing their ROI while decreasing operational costs.

Work Order Management

Cantier CMMS keeps track of Preventive maintenance (PM) schedules, Corrective maintenance (CM) and Predictive Maintenance (PdM) actions through work orders, allowing companies to quickly respond to unplanned downtimes as well as monitor maintenance schedules.

• Maintain a list of all pending and open work orders
• Create maintenance schedules with tasks and frequency
• Automatically set PM schedules based on PM definitions
• Assign technicians to perform preventive, corrective maintenance
• Automatically schedules maintenance work orders when predictive maintenance incident occurs based on Condition based and Usage based parameters or Historical data.
• Request spare parts and supplies for maintenance orders
• Report equipment problems in real-time start, put on-hold, report progress, complete, and buy-off maintenance orders
• Configurable to stop the equipment when Out of Controls of usage based and condition based parameters or if the scheduled maintenance is not happening as planned.

Equipment Logs

Cantier CMMS keeps track of equipment availability and activity to provide supervisors and managers accurate data of their machines. CMMS can also directly link with the equipment and create real-time equipment activity logs automatically.

• Keep track of equipment status and activity real-time
• Determines downtime and unavailable hours based on logs
• Can be done through Equipment Connectivity using IIoT gateway

Equipment Problem Knowledge-base

Cantier CMMS keeps a repository of common equipment problems for machines, along with associated tasks and corrective action, allowing companies to standardize maintenance action and streamline repairs.

• Maintains a list of equipment problems for all machines, along with tasks and supplies
• Creates a flexible repository of work instructions for all equipment problems
• Reports aid supervisors on equipment problem analysis
• Defines specific problems per machine or per part

Spares Requirement Planning

Cantier CMMS breaks down preventive maintenance schedules and generates requirement plans for spare parts and supplies, in order to ensure that all maintenance schedules as well as unforeseen breakdowns are dealt with quickly.

• Maintains a list of equipment problems for all machines, along with tasks and supplies
• Generates an SRP based on the maintenance schedule and required Spare parts and supplies
• Tracks spares part inventory and requirements to determine purchasing quantifies and schedules

Maintenance KPIs
CMMS helps monitoring your Key Performance Indicators (KPI) such as OEE, MTBA, MTBF, MTTR. The same KPIs are the key metrics of TPM, a methodology aimed at forming a corporate culture focused on Maximizing the Efficiency of the Overall Production systems through teaming and empowerment

Recipe Management System (RMS) plays a vital role in SMART Manufacturing when it is completely automated with two way communication between Equipment and MES. RMS is tightly integrated with the Product Configuration and it allows to identify the right recipe automatically when the lot or Batch move to a station or equipment. It provides alert or even stop the machine when there is wrong recipe selected by an operator.

RMS validates the recipe data against Lot or Product or equipment quickly and download or upload recipe files to SEC/GEM supported machines. Also, it allows to download or upload recipe parameters to PLCs. This validation and real-time upload and download features prevent faults, increase throughput and yield. It helps to compare parameter values between different versions of recipes in real time and historical values as well. Reports available to compare the performance KPIs against different versions of recipes.

RMS maintains a centralized Recipe Library across the factory to store and transact the recipes securely. With the help of Cantier SPC, Recipe parameters vs Output parameters is monitored real-time and provide the trend report. When there is a downward trend, they RMS alerts the users to look at the recipe values for adjustments.

OEE (Overall Equipment Effectiveness) is a key metric to measure the productivity in the shop-floor and it becomes a manufacturing best practice. By accurately measuring OEE, companies can quickly see how effectively a manufacturing operation is utilized and thereby establishing continuous improvements in the factory by eliminating wastes (i.e., Lean Manufacturing).

Real-time data collection becomes essential to come up with the accurate OEE. This can be achieved with the latest technologies and tools available. The three components of OEE are Availability, Performance and Quality.

Availability
It represents the percentage of planned time that the operation is available to operate. Availability accounts for all the losses that happened during the planned production time such as equipment failures, material shortage, setup time, etc.

Cantier OEE measures availability information from CMMS module and real-time communication with the Equipment through OPC, OPCUA, SECS/GEM communication protocols. Cantier IIoT gateway securely manages all these communication and data collection. Downtime logs are captured and alert the operators as it happens.

Performance
The speed (actual cycle time) at which the machine runs vs its designed speed (Ideal Cycle time). Performance is calculated from how much waste is created when running at less than optimal speed. By looking at actual cycle time vs Ideal Cycle time, we can determine how much production was lost in a particular lot or within a specific interval.

Cantier OEE measures the performance by collecting the actual cycle time directly from the machines and compares it with the ideal cycle time defined in the Product configuration and Equipment set up. Real-time communication with the equipment provides accurate performance real-time.

Quality is a measure of the Good Units produced as a percentage of the Total Units Started. Quality loss include scrap or defect and units that need rework.

Cantier OEE measures Quality by collecting the data from the WIP module and directly communicating with Metrology equipment through IIoT Gateway.

Manufacturers are leveraging on IIoT that plays a vital role across all manufacturing data to improve their operational efficiency, quality improvements, and equipment effectiveness. Cantier SPC, WIP, CMMS, RMS & OEE modules collect huge amount of data during the production processes like machines used, operators, materials, defects, in-process quality data, recipe parameters, equipment availability, equipment performance, and others.

In order to fully understand their shop floor, Cantier Manufacturing Intelligence (MI) analyzes the data with context. Cantier MI provides just the right amount of the right information to the right role at the right time to allow them to make the right decision and take immediate action. Cantier MI can help manufacturers make timely decisions with KPI-based dashboards and reports. MI communicates across systems and perform autonomous actions. It predict issues by applying artificial intelligence and machine learning technology.

SMART Control Room
Manufacturers are leveraging on IIoT that plays a vital role across all manufacturing data to improve their operational efficiency, quality improvements, and equipment effectiveness. Cantier SPC, WIP, CMMS, RMS & OEE modules collect huge amount of data during the production processes like machines used, operators, materials, defects, in-process quality data, recipe parameters, equipment availability, equipment performance, and others.

Machine Learning (ML)
Machine learning presents its opportunities by looking at any situation to derive new knowledge from the past experience, using their petabytes of historical data. By using various statistical methods and deep learning, the technology identifies recurring patterns and apply the results to the new transactional data streams. Cantier Manufacturing Intelligence detects trends in real time and predicts upcoming failures. Although Machine Learning can be applied in various data that are collected from the IIOT devices and Sensors, Cantier MI is focused on the following key areas where manufactures save cost tremendously with shorter period of ROI.

Equipment Failures and Predictive Maintenance
Usually, maintenance is conducted either by time based (Preventive) or when problem occurs (Corrective). In preventive maintenance, machines still have chances of failure before the actual schedule as the resources may have used more than the regular usage. In corrective maintenance, no choice but to schedule for a repair work with the loss of production hours.

With the historical equipment failure and downtime data collected, Machine learning identifies the patterns of equipment or equipment’s part failure and determines when the actual maintenance should occur to avoid breakdowns. Cantier MI provides necessary alerts in advance and creates work orders for such maintenance activities.

Machine Learning on Quality Control
Though there are still manual inspections to identify quality issues, mostly measurement equipment is used to inspect parts and products manufactured in the plants. Machine Learning is applied to the historical data of both input parameters (recipes) and output parameters and establish trends and patterns. This patterns helps to predict the quality issues during the production and eliminates wastes. Cantier Manufacturing Intelligence alerts the operators and supervisor when there will be potential quality issues.

On the other hand, Machine Learning can also be used to visually inspect products and identify flaws much faster than how it is manually done by human. Examples: Cracks, Misaligned Labels, Misalignments, etc.

Machine Learning on OEE
ML plays a key role in improving OEE by looking at the historical data. This metric measures the availability, performance and quality of manufacturing equipment, which are all improved with the integration of deep-learning neural networks that quickly learn the weaknesses of these machines.