IOT solutions manufacturing, warehousing, data visualisation

Industrial automation & measurement

January 4, 2019ripplesiotData visualisation, IOT asset tracking, IOT in factories, IOT in manufacturing

IOT & activity based costing

How Condition Monitoring solutions can lead to a higher ROI

Activity Based Costing is widely used in the manufacturing industry. However, it comes with its fair share of criticism because it is difficult to correctly estimate the amount of resources required to perform a task efficiently.

Two of the key performance indicators (KPI) in the manufacturing industry are MTBF (Mean Time Between Failures) and MTTR (Mean Time To Repair). MTBF is a performance metric that measures the time elapsed between when a failure occurs and the next time it happens. MTTR is the time spent to conduct repairs once a failure occurs. Both these KPI’s are calculated by dividing the total time taken respectively by the number of failures. While these are good indicators of performance, they are flawed. Failures cannot be foreseen as they are not uniform and can occur at any point of time. In the case of repairs, it may take longer for some than others. That is why these metrics lack real-life accuracy.

Using condition monitoring solutions, it is possible to successfully obtain operational information from machines which are variable in nature. The actual operational times of the machines can be analysed and resources can be allocated accurately. Maintenance can be scheduled based on the number of hours used. This eliminates the need to estimate KPIs like Mean Time Between Failures and Mean Time To Repair by providing us actual figures of usage. No excess resources will need to be allocated . This will in turn improve operational efficiency and ultimately lead to a higher Return on Investment (ROI).

IOT solutions can help to improve the audit and scheduling of pro active maintenance schedules by gathering operational data such as hours used, operating environment, power consumed and abnormal handling of equipment by users. Helps to ascertain Mean Time Between Failures (MTBF) and Mean time Between Repairs (MTBR)

Most of factories and warehouses employ technical staff to conduct periodic check and repairs to ensure the asset equipment are up and running all the time. Unexpected breakdowns can lead to loss in revenue, opportunity costs, unsatisfied customer etc. Using our IOT in maintenance solutions, your own technicians will be able to remotely monitor the fixed assets to help prevent breakdowns.

IOT industrial automation & maintenance

Implementing a retrofit IOT solution with non invasive sensors and integrating data visualisation tools can help businesses to improve equipment uptime, track and trace of critical plant and machinery in factories, shipyards, airports, supply chain environment, warehouses etc, which otherwise takes many man hours of unproductive work.

Anomaly detection solutions for industrial automation can help businesses improve the operational excellence by pro active maintenance, optimising spares inventory and reducing energy consumption of various heavy industry equipment.

Call us at the following numbers to more on how IOT industrial automation sensors and IOT in maintenance management using anomaly detection solutions can help improve asset efficiency and reduce breakdowns.

Measure & monitor legacy machines

December 23, 2018ripplesiotData visualisation, IOT in factoriescurrent monitoring, equipment utilisation

IOT for industrial monitoring & cost savings

Legacy plant and machinery in many factories lack the technology to bring machine intelligence on operational factors that govern their performance, utilisation and accounting practices to help achieve industrial cost savings. With the advent of wireless sensors, mesh technology and open source data visualisation tools, deploying such solutions have become easy and affordable. Let us discuss a few of the factors

Measuring power consumption of critical equipment

Implementing an activity based costing methodology in a manufacturing or services environment would need to know the cost incurred on each equipment. For this purpose, our modules provide the power consumed by your legacy machines.

Monitor utilisation of high value equipment to ensure productivity

The hours used by each of the legacy equipment will be helpful for the plant manager schedule proactive maintenance and stock consumables and spares accordingly.

Wear and tear of machines to provide proactive maintenance

Using vibration and other models, data visualisation tools can help the shop floor managers detect anomalies in the critical components of plant and machinery.

Environment monitoring in factories

People health, safety play an important role in the productivity of any organisation. It is more so in the manufacturing sector, where the air quality – dust, noxious vapours, humidity etc play a big role.

Inventory management and cost savings

Timely availability of resources, at the right place can help shave a few cents from the factory operations. Industrial tracking solutions for assets and people will help in improving production workflow and supervision.

Industrial cost savings using IIOT solutions

Wireless mesh networks can be deployed inside factories and warehouses to save on the deployment and maintenance costs. Besides, retrofit solutions ensure quick deployment (in under 30 minutes in most cases). Long battery life of solar powered solutions further reduces the cost of ownership.

Check out the industrial cost saving, factory equipment monitoring and asset tracking solutions from RipplesIOT

Air quality & PM

October 27, 2018ripplesiotAir quality sensors, Data visualisation, IOT solutions

Why air quality monitoring is important

Particulate Matter, abbreviated as ‘PM’, is a mixture of airborne solid particles and liquid droplets that can be inhaled by human beings, and may cause serious health problems in industrial zones. PM includes particles with different characteristics – i.e. shape, optical properties, dimension and chemical composition – but it is mostly divided into finer categories based on the particle size information.

Now a days, different PM categories are usually reported under the common nomenclature of PMx, where ‘x’ defines the maximum particle diameter in the airborne particle mixture or ‘aerosol’. As an example, PM2.5 defines inhalable particles with a diameter of generally 2.5 micrometers (hospital hygiene as an example) and smaller, PM10 particles with a diameter of 10 micrometers and smaller, and so forth for other applications.

Ripples IOT provides wireless environment monitoring solutions based on high precision air quality dust sensor capable of detecting 0.5µm particles. Compared to other vendor models, our solutions have the capability to intake and analyse greater air volume, providing more consistent and accurate results for environment air quality monitoring.

Where air quality & PM matters

Air quality monitoring solutions - Singapore

The specific PM categories of PM10 and PM2.5 have been historically identified by governments in developed nations as important monitoring levels to assess the quality of the air we breathe in industrial and domestic zones. PM10 particles irritate exposed mucous such as the eyes and throat and PM2.5 particles travel all the way through the lungs into the pulmonary alveoli (the basic unit of mammal ventilation).

New categories like PM1.0 and PM4.0 are also finding their way into indoor air quality monitoring devices as these new outputs provide additional information to the traditional PM10 and PM2.5 levels, enabling a better particle pollution analysis in manufacturing shop floor, warehouses, public health zones etc and the development of new air quality device specific actions based on the detected aerosol type (e.g. industrial dust vs. kitchen smoke).

The common definition of PM includes particles that are no smaller than 100 nanometers in size. Particles smaller than 100 nm are instead reported as ‘ultrafine particles’ or ‘UFPs’ and are not covered in this article. Within the above-mentioned PM definition, which thus includes particles from 0.1 to 10 micrometers in size, the smaller the particles are, the deeper they can penetrate through our respiratory system and into our bloodstream, posing a higher hazard to our health.

The World Health Organization (WHO) reports that airborne particulate matter as a Group 1 carcinogen and as the biggest environmental risk to health facing humanity now, with responsibility for about 1 in every 9 deaths annually.

RipplesIOT provides easy to deploy, mesh technology enabled air quality monitoring sensors and data visualisation and alert tools which can be deployed in factory shop floors, warehouses, offices, hospitals and public utility buildings.