OPTIMUS

Data. Digitalisation. Decision.

As legendary management consultant Peter Drucker famously said “What gets measured gets improved." Enabling the capability to make data-driven-decision by measuring production performance is the ultimate goal of Optimus. With quantifiable production information, factory can measure its performance for continuous improvement. Optimus powers the digitalisation process in manufacturing process by direct integration with machine PLC, sensors, measurement instruments via various communication protocol. Without data, the journey towards industry 4.0 is not possible..

One relatively quick benefit you can easily achieve with Optimus is putting data-driven decision matrix into your manufacturing process. For example, once you can measure OEE effectively, you can

  1. benchmark yourself against industry standard

  2. measure yourself in the effectively of autonomous maintenance and preventive maintenance

  3. measure your improvement in machine utilisation. All these are important to minimise cost of manufacturing.

There are many other KPIs in Optimus which can be essential to any manufacturing plant, for example MTBF (mean time between failures), OTIF (on time in full), CPK (process capability index), etc. All this KPIs, once quantified, will propel your manufacturing to the next level of operation maturity and improve your production efficiency.

Optimus ® is the trademark owned by

InnoArk Pte Ltd in Singapore.

What is digitalisation for manufacturing?

The scope of Industry 4.0 is gigantic, from integration, big data, automation, data science, augmented reality, security, internet of things (IoT), edge computing, cloud computing, machine learning, etc. Not everything is applicable to every manufacturing environment. First and foremost, is for your factory to determine which is applicable based on the maturity of your manufacturing process. Regardless of which path you choose, digitalisation of your production information is always one of the first few steps towards this goal.

Data is present in your machine PLC, HMI, sensors, online and offline instrument, etc. Optimus focus is in aggregating all these data to enable you to make data-driven decision based on comprehensive and well anlaysed information from Optimus. With our 15 years of experience in digitalisation for manufacturing process, we know what data you will need in order to measure your performance matrix.

 

In Industry Europe Magazine, Oct 2018 issue, InnoArk was mentioned by our client in the UK. As what Dr Ian Tindall of Cerulean (UK, Milton Keynes) says : “InnoArk delivers some of the data analytics and predictive maintenance advantages of Industry 4.0.” This is exactly what we do with data from machines.

To achieve this, below are the 3 main sources of data in a typical manufacturing process as shown below. Each of the 3 can be done independently to fit your manufacturing needs.

1) Machine data (PLC, HMI, SCADA)

and other manufacturing system data

PLC (programmable logic controller) is normally the brain behind every machine. Some PLCs are attached to HMI (human machine interface) where information in PLC can be tapped from the HMI as well. Optimus can extract data from various PLC and HMI with established protocol, including the brand below, in collaboration with HMS.

Some manufacturing data can also be available in SCADA (Supervisory control and data acquisition) or in other process control systems. Data from these systems is generally well defined and ready for data extraction. Optimus can integrate with these systems for data extraction using established protocols.

 

The data that is typically available in this area are machine start / stop time, output quantity, error code, motor rpm, oven temperature, air flow speed, etc. This data is essential in deriving OEE (Overall Equipment Effectiveness) which is a common measurement matrix for machine utilisation across industry. On top of OEE, this valuable data can be further analysed for loss tree analysis combing with product wheel mapping.

2) Sensors, in-process & offline

instrument data

Sensors are commonly used in manufacturing lines for enhancing machine capability and process control. Instruments are typically use for measurement of product quality, be it online or offline.

 

Sensors

Optimus solution is coupled with Optimus sensors whose data can be readily aggregated into Optimus data platform.

Typical sensors used in manufacturing process are

  • temperature sensors (monitoring heating chamber, oven, drying process, etc)

  • proximity sensors / counters (monitor quantity produced before and after rejects)

  • vibration sensors (monitor rotating parts , motors and trigger alert when there is abnormal vibration pattern)

  • Current sensors (non-invasive, monitor electricity consumption and trigger alert when there is abnormal usage pattern)

 

Our experience in selecting the appropriate sensors and knowing the location to put in sensors is critical in ensuring the right data is collected without causing trouble to your existing manufacturing line. Data from sensors can get stored in your factory or in cloud-based Optimus for easy remote monitoring as well.

In-process and offline instrument

Very often online and offline instrument data are critical for troubleshooting to improve machine performance. Reason being any slightly malfunctioning of machine will cause product quality to display abnormally. For example, if filling machine in snack packaging is slightly malfunctioning, the content weight will be affected which can be detected if there is a online weight checker. Hence having instrument data can enhance the speed of decision making process.

For online instrument, data like thickness (sheet product), temperature, moisture (near-infra-red technology), element composition (X-ray fluorescence technology), weight, etc, can be extracted directly from most instrument using TCPIP or RS232 cable. 

 

For offline instrument, instrument like gas chromatography (GC), High-performance liquid chromatography (HPLC), the data can be readily extracted from the built-in computer with correct data mapping.

INCREASE THROUGHPUT

INCREASE PRODUCTIVITY

ENHANCE DECISION MAKING PROCESS

REDUCE

DOWNTIME

ELIMINATE COST OF REPLACING BROWN FIELD MACHINERY

How That Helps You

3) Environment data

If you are in food or pharmaceutical manufacturing industry, a well-controlled environment is critical for your production line as well as your warehouse, fridge, freezer etc. 

Optimus uses industrial grade calibrated sensors and brings together IoT (Internet of Things) platform to empower you with the capability to monitor environmental conditions remotely. It alerts you when your environment condition is not performing in optimal way. This can be viewed remotely via dashboard and alerts on laptop and mobile devices.

How does it work?

Accurate monitoring of critical parameters via internet with Optimus. If any measured data goes beyond the limits you set, you will be notified.

3 Easy steps to start using

 

  1. confirm the location to be monitored and inform us the quantity of devices needed

  2. receive the devices and connect them to internet (using wifi or data-only SIM card)

  3. put the devices at the targeted location and start monitoring

4) Data integration with ERP, MES, LIMS & other systems

Data integration with other manufacturing systems, for example, ERP, MES, can be done with Optimus using your existing middle ware to minimise IT landscape. Optimus has already a huge pull of database that is readily to be mapped into data from various sources for data analysis.

 

When one performs data integration for manufacturing processes, having in-depth knowledge of manufacturing processes is essential to ensure efficient and accurate data extractions. In Optimus, we are well equipped with this. Having spent the last 15 years in FMCG manufacturing processes, we have built thousands of manufacturing parameters in Optimus that are typically used in manufacturing processes.

 

In some cases, Optimus is required to integrate with SAP to extract bills of material information for validation of materials as well as process specification management. The ultimate objective is to enable comprehensive data analysis to improve manufacturing performance.