On Tuesday, March 20, LNS Research hosted the webcast, “Industry Standards as Building Blocks to Quality Maturity and Operational Excellence.” The presentation examined how to use industry standards to capture the attention and cooperation of senior corporate executives, the capabilities required to achieve competitive advantage through quality, and the results companies should expect.Read More
Over the past few months, we’ve been helping many LNS program members with strategic planning for 2018, and underlying this planning is a common theme - “What is the perceived value of quality?”Read More
LNS Research is thrilled to launch the first Analytics That Matter survey in partnership with MESA (Manufacturing Enterprise Solutions Association) International. For the last six years we partnered with MESA on the Metrics That Matter survey, which has been one important foundational element of LNS Research’s primary data-driven research. As the use of plant-centric data has expanded dramatically since the last survey in early 2016, we decided to change the focus from overall metrics to the use of analytics in manufacturing operations and beyond.Read More
Tags: Metrics, Manufacturing Operations Management (MOM), Big Data, Benchmarking, Overall Equipment Effectiveness (OEE), Mobile / Mobility, Manufacturing Execution System (MES), Industrial Internet of Things (IIoT), Asset Reliability, Digital Transformation, Industry 4.0 / Smart Manufacturing, Artificial Intelligence / Machine Learning (AI/ML), Asset Performance Management (APM)
It's no secret that companies that benchmark performance against actual practices in operations, quality, environmental, safety, risk management, energy, and many others are able to drive and sustain higher performance levels, and contribute meaningful value to enterprise objectives. Even companies that are long-time pros at benchmarking performance in these areas often struggle to pinpoint best practices that have a beneficial impact on new product introductions (NPI). When so much is at stake, what's holding them back?
The fact is, the pressure is on and growing for manufacturers:Read More
For those who are unaware, every two years here at LNS Research we engage with MESA International to conduct the “Metrics that Matter” research study – focused on identifying the most important and cutting edge trends in manufacturing; particularly on the key performance indicators (KPIs) that companies are using as well as the improvements displayed therein.Read More
GE Invests in Sight Machine to Build out Big Data and IIoT Capabilities
GE Ventures, the start-up collaboration division of General Electric, has invested $13.5 million in Sight Machine, a manufacturing analytics solution provider with customers in the automotive, life sciences, and consumer goods industries. The move comes as part of the industrial/IT giant’s initiative to gain more data from factory floor machines and assets, and as a part of its larger strategy to shift toward a digital company at the forefront of Industrial Internet of Things (IIoT), which was signaled in its September 2015 announcement of the GE Digital business segment.Read More
We at LNS Research have spent the past several years researching, writing, advising, and consulting on Big Data Analytics in the industrial sector. As part of our Metrics that Matter research we have shown how manufacturers believe areas like business model transformation and asset value.Read More
As we move into 2016 with high hopes for manufacturing in general and the industrial software industry in particular, we are delighted to announce the fourth installment of the Metrics That Matter (MTM) survey jointly presented by MESA International and LNS Research.Read More
The LNS Research Asset Performance Management (APM) survey has clearly shown by almost 50%, that the number-one goal to improving asset performance within an organization is to have better operational performance. So, now the questions to ask and discuss are:
- How do I, as an APM software user, prove that our organizations investments in the APM landscape are working?
- How do I prove this by providing visibility within the department all the way up at the senior level of the organization to make sure this is the case?
As organizations look to improve their maintenance effectiveness, many have taken the step of identifying critical production assets and collecting actual operational data such as run times and cycle counts on those assets. Often this is done automatically by linking to the programmable logic controller (PLC) or similar level one control element. In other cases, a process data historian or MES or MOM application may link to the process automation equipment and will then serve as the bridge to move that data into the APM environment.