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Integration of Keyence (Image Dimension Measuring System – IM Series) and SPC System

Category : Blogs

Integration of Keyence (Image Dimension Measuring System – IM Series) and Blue Ocean Real Time SPC System

The solution is an integrated offering from two of the leading providers of industrial measuring equipment and software. A breakthrough solution that provides you with timely, accurate exchanges of consistent information between Keyence Image Dimension Measuring System and Blue Ocean Real Time SPC systems to support both your strategic quality and process control goals.

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Integration of Mitutoyo Wizhard Hardness Tester and SPC

Category : Blogs

Integration of Mitutoyo Wizhard Hardness Tester and Blue Ocean Real Time SPC System

The solution is an integrated offering from two of the leading providers of industrial measuring equipment (Mitutoyo) and software (Blue Ocean Data Solutions). A breakthrough solution that provides you with timely, accurate exchanges of consistent information between Mitutoyo Wizhard Hardness Tester and Blue Ocean Real Time SPC systems to support both your strategic quality and process control goals.

Using the combination of Mitutoyo Wizhard Hardness Tester and Blue Ocean Real Time SPC systems, the real-time data generated by SPC system is available for storage, transformation (into information, not data), visualization and analysis. If there is SPC violation, real time alert will be triggered which enable quality engineers to take immediate actions. This integrated system will empower engineers to focus on continuous quality improvement and cost reduction which eventually will lead to greater customer satisfaction.

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This integrated solutions will provide real-time Operations information and the tools to manage, and your analyze quality performance to increase your company competitive advantage.

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This integration provides you with real-time visibility into your quality operations, enhancing your agility and flexibility to respond to operational issues that can impact your business performance and financials.


What is Overall Equipment Effectiveness (OEE) ?

Category : Blogs

Most industries have some kind of performance indicators on their equipment such as up time, units produced, and sometimes even the production speed. These are appropriate things to look at if the focus is on what’s coming out of the machine.

Total Productive Maintenance (TPM) takes a slightly different approach. Besides what’s coming out of the machine, we also want to know what could have produced, and where we are losing effectiveness. Overall Equipment Effectiveness, or OEE, offers a simple but powerful measurement tool to get inside information on what is actually happening.

The OEE calculation is a metric that gives us daily information about how effectively the machine is running and which of the six big losses we need to improve. Overall equipment effectiveness is not the only indicator to assess a production system, but it is certainly very important if our goal is improvement.

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The Elements of Overall Equipment Effectiveness (OEE)
The three main categories of equipment-related losses —downtime, speed loss, and defect or quality loss— are also the main ingredients for determining the overall equipment effectiveness. Overall equipment effectiveness is calculated by combining three factors that reflect these losses: the availability rate, the performance rate, and the quality rate.

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To calculate OEE, we multiply the three factors together:

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Benefits of OEE Monitoring
The goal of measuring OEE is to improve the effectiveness of your equipment. Since equipment effectiveness affects shopfloor employees more than any other group, it is appropriate for them to be involved in tracking OEE and in planning and implementing equipment improvements to reduce lost effectiveness. Let’s look at some of the benefits of OEE measurement for a manufacturing company.

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An OEE solution can enable manufacturers to achieve world-class status. More specifically, it can provide benefits in three key areas:
1. Equipment: Reduced equipment downtime and maintenance costs, plus better management of the equipment life cycle
2. Personnel: Labour efficiencies and increased productivity by improving visibility into operations and empowering operators
3. Process: Increased productivity by identifying bottlenecks
4. Quality: Increased rate of quality, reduced scrap



What is Statistical Process Control (SPC)?

Category : Blogs

Statistical Process Control (SPC) is a scientific, data-driven methodology for quality and process improvement. It removes guesswork out of quality control.

Statistical Process Control (SPC) is a statistical technique for measuring and controlling product quality. It is applicable for in-coming, in-process and out-going quality control. Quality data in the form of Product or Process measurements are obtained in real-time during measurement. This data is then plotted on a graph with pre-determined control limits. Control limits are determined by the capability of the process, whereas specification limits are determined by customer.

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Data that falls within the control limits indicates that process is operating as expected. Any variation within the control limits is likely due to a common cause—the natural variation that is expected as part of the process. If data falls outside of the control limits, this indicates that an assignable cause is likely the source of the product variation, and something within the process should be changed to fix the issue before defects occur.

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Benefits of Blue Ocean Real-Time SPC System :
Dramatically reduce variability and scrap
Scientifically improve productivity
Reduce costs
Uncover hidden process personalities
Instantly react to process changes
Make real-time decisions on the shop floor

How to quantify the ROI of a Real-Time SPC System

To quantify the return on your SPC investment, start by identifying the main areas of waste and inefficiency at your facility. Common areas of waste include scrap, rework, over inspection, inefficient data collection, incapable machines and/or processes, paper-based quality systems and inefficient lines. You can start to quantify the value of an SPC solution by asking the following questions:
Are your quality costs really known?
Can current data be used to improve your processes, or is it just data for the sake of data?
Are the right kinds of data being collected in the right areas?
Are decisions being made based on true data?
Can you easily determine the cause of quality issues?
Do you know when to perform preventative maintenance on machines?
Can you accurately predict yields and output results?
For more detailed information about Blue Ocean Real Time SPC System, please contact us for system demo.


Challenges of Effective SPC Implementation

Category : Blogs

Challenges of Statistical Process Control (SPC) Implementation In Malaysian Manufacturing Companies
Introduction

For the past ten years, Malaysian manufacturing companies facing tough competition especially due to rising customer expectations on product quality, better services and lower production cost from the countries in this region such as Thailand, Indonesia ,Vietnam, etc.
SPCImplementationPic1 In order to compete and survive in global competitive market place, Malaysian manufacturing companies are trying hard to improve their product quality, cost competitiveness, efficiency, productivity and technology.

In view of quality expectation from customers is getting higher, manufacturers can’t rely on traditional quality management approach which is very much focus on corrective action or “fire fighting”. Engineers need to be more proactive to prevent defects or rejects being produced.

In recent year, the use of Statistical Process Control (SPC) and statistical method is emphasized. Nowadays, it becomes a mandatory requirement for most of the contract manufacturers. The use of SPC and statistical methods for variation reduction are core philosophies of Continuous Improvement and Total Quality Management.

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Traditional quality control suffers in that it is reactive to problems with an overemphasis on inspection and sorting. Continuous improvement philosophies are proactive with a focus on prevention and early detection of problems. Continuous improvement philosophies are data – driven with the use of defendable statistical methods for diagnosing problems.

SPC, Design of Experiments, and the use of statistical methods to quantify variation are key principles of the more contemporary Six Sigma Quality and Lean Six Sigma (LSS) philosophies. Six Sigma Quality and LSS philosophies promote reduction in long term variation so that only 3.4 parts per million defective are manufactured. What business person would disagree with such philosophies?

Challenges

Although the role of SPC is critical to achieve better product quality, however the implementation of SPC in most of the Malaysian manufacturing companies is not satisfactory. Traditional way of implementing SPC is no longer suitable in today highly competitive market place.

Typically, when a manufacturer implements a quality control procedure that involves measuring something, they start by purchasing a measuring instrument (e.g. a caliper, micrometer, height gage, bore gage, force gage, CMM, etc.) from one of the many metrology companies. The manufacturer might then develop a procedure for measuring their parts where someone is given the task of taking measurements and writing them down on a piece of paper. The measurements would then be keyed into either a spreadsheet or a dedicated SPC software program for analysis by an engineer. Obviously this method has a lot potential pitfalls since people are involved in the manual data collection and data entry part of the process. Manual data entry is slow and tedious and people make mistakes.

Possible Solutions

A more accurate and more efficient approach to data collection is to enter data from your measuring instruments directly into a spreadsheet or SPC program. Most measuring tools today are available with some form of electronic output making it possible to connect the instrument to data loggers, printers or to a computer, thereby eliminating the steps of manually writing down measurements and typing them in.

Automating data collection removes all possibility of human error and it also allows for real time data analysis. In addition to collecting an accurate computerized record, it is also possible to control an entire process based on the input from the tools that you use to measure the process. From our previous example, when you measure each part that comes out of your cutting machine, the measurement can be fed immediately to a PC that has been programmed to instruct an operator to change the blade when the measurements fall outside a specific tolerance. This type of automation creates an extremely efficient process designed to maintain the manufacturers’ quality control standards.

Interestingly, the metrology industry has never settled on any one standard for the electronic interface between instruments. This is due, in part, to simple rivalries between companies. Each of the different “key players” in the measuring tool industry developed their own electronic interface with the hope of making theirs’ the standard for the entire industry. By protecting their interface standard with patents, they lock the competition out from any large manufacturer that adopts their electronic interface standard.


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Blue Ocean Cloud Based Smart SCM

Category : Blogs

Today’s business supply chains for complex products are likely to involve a number of autonomous organizations. The competitive market requires that these supply chains are highly agile, effective and efficient. Agility and effectiveness are obtained by forming highly dynamic virtual enterprises (VE) within supplier networks. All these highlight the importance of information technology in integrating suppliers and other partners’ firms in a virtual enterprise and supply chain.

Blue Ocean’s Approach and Technology
Supply chain management (SCM) is a way of obtaining horizontal integration benefits without its formal ownership costs. SCM, the integration of key business processes among industry partners, adds value to customers, tightly links together several consecutive elements of the industry value chain, from upstream suppliers, to subassembly manufacturers, to final manufacturers, to distributors, to retailers, to end-customers.

Below is the diagram of proven Blue Ocean Cloud-Based Supply Chain Management System. Cloud tools can bring a lot of value to an organization. Thanks to their inherent flexibility and very low start- up cost. The below mentioned SCM system going to help an organization to increase operation performance and profitability.


Big Data Analytics for Manufacturing

Category : Blogs

What is Big Data Analytics?

The industrial internet of things (IIoT) is changing the way we live and work, and extracting maximum value requires a big data approach.

 

The industrial internet of things (IIoT) is an exciting outcome of the digital revolution that is changing the way we live and work. Many organisations already focus on how to benefit from it, but extracting maximum value requires a big data approach.

Operational savings and revenue opportunities


Through the IIoT, operations technology and information technology will blend together and become more intelligent through the use of sensors, analytics and machine applications – a development that will share and create even more data. The insights gleaned from this big data and new types of data can bring many benefits for businesses, including operational savings and revenue opportunities.

For example, research has indicated that predictive maintenance can generate savings of up to 12% over scheduled repairs, leading to a 30% reduction in maintenance costs and a 70% cut in downtime from equipment breakdowns. For a manufacturing plant or a transport company, achieving these results from data-driven decisions can add up to significant operational improvements and savings opportunities.

Blue Ocean’s Approach – Big Data Analytics

The key challenge for organisations is to drive actionable insights and, ultimately, incremental value from data generated by IIoT. To do so, organisations must think about how they collect, store and analyse that data.

The good news is that setting up a big data platform to leverage IIoT can be done incrementally without needing a big up-front investment.

We recommends that organisations begin implementing their big data strategy in an agile way with a small proof of concept. This approach will show them which data combinations generate the most value before they scale into a broader enterprise solution. Cloud-based approaches are also becoming more common because they provide greater flexibility to scale up and down as the business need evolves.

Big Data Analytics For Manufacturing

 

      1. Example of Big Data Analytics Dashboard for OEE Monitoring
        Below system captures machine data from the source. After data compilation and making use of big data processing technology, it able to provide management with real time information on what happening in the shop floor. Quick response and actions can generate significant cost saving and revenue opportunities.

     

    1. Example of Big Data Analytics for Process Study
      Below data is captured through real time in process measurement system. Through big data analytics technology, it enables process and quality engineers to perform real time process troubleshooting and quality analysis for quality improvement and process optimization.

    Variability Chart for DIAMETER

     


Industry 4.0

Category : Blogs

Industry 4.0 is a name for the current trend of automation and data exchange in manufacturing technologies. It includes cyber-physical systems, the Internet of things (IoT), cloud computing and cognitive computing.

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Convert PDF drawing to AutoCAD in one click

Category : Blogs

Struggle with Read -Only (Or Non-Editable) PDF Engineering Drawing?

Convert PDF drawing to AutoCAD in one click!
Very often, contract manufacturers will receive read-only (or non-editable) engineering drawing from customers. This ended up engineers take hours to re-generate AutoCAD drawing which is editable for production and in-process QC inspection purposes.

Blue Ocean PDF converter is an industry leading PDF to AutoCAD software that is the most accurate solution available today. By using this solutions, users can convert PDF drawing into DWG formats where it can be used and edited as required.

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Comprehensive functions & features:

During drawing conversion process, it provides additional value such as:
1) Enable to modify and edit AutoCAD drawing after convert from PDF drawing to CAD drawing,
2) Changes of drawing scale,
3) Selection of certain drawing object or page for conversion, etc

Other than conversion of pdf drawing to AutoCAD, it also support other document types such as Word, Excel, PowerPoint, HTML and numerous other formats.

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Convert PDF Drawing to AutoCAD in One Click

Click Here to view in PDF format

For more information, please contact:
Blue Ocean Data Solutions Sdn Bhd
(Manufacturing Solutions Specialist)

KL office:
Unit No. 12-02, Block A, Zenith Corporate Park, No. 1, Jalan SS 7/26, Kelana Jaya, 47301, Petaling Jaya, Selangor Darul Ehsan.
JB office:
23-03, Block B, Kompleks Austin Perdana (V-Square), Jalan Austin Perdana 2, Taman Austin Perdana, 81100, Johor Bahru, Malysia.

Contact Person: Mr Bong KL (Technical Manager),
Handphone: 013 7277606
Tel : 07-3512160
Email: bongkl@blueoceands.com
Website: www.blueoceands.com


Contact Us Now!