Manufacturing and IT leaders have been pursuing IT-OT convergence strategies for many years now. To reach that converged state, LNS Research sees establishing a common data model including both IT & OT data as an essential step. This common data model ensures that the data leaving the plant from multiple sources and of multiple types are accurate, trusted, and secure.
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Recent Posts
Survey Snippets #2: Two Best Practices in Leveraging a Common Data Model to Enable IT-OT Convergence
Posted by Vivek Murugesan on Mon, Jan 25, 2021
Categories: Industrial Transformation / Digital Transformation, IT/OT
New! Survey Snippets: How Analytics Leaders Manage Metrics
Posted by Vivek Murugesan on Tue, Jun 23, 2020
Introducing Survey Snippets
LNS Research has started a blog series called Survey Snippets that will include call-outs from our recent survey data and compelling insights for manufacturing executives. The first blog post of this series is about analytics’ role in a company’s Industrial Transformation (IX) program, and how leaders in this field are leveraging metrics to distinguish themselves from the rest.
Read MoreCategories: Industrial Transformation / Digital Transformation, Survey Snippets, Industrial Analytics
Two Sides of the Same Industrial Transformation Coin: APM 4.0 and Factory of the Future
Posted by Vivek Murugesan on Thu, Oct 24, 2019
The relationship between asset performance and operational performance are well known and pervasive. All too often, however, companies manage them in sub-optimized in silos. Recent discussions with clients clearly reinforced our insight that operating in silos is counter-productive to industrial transformation (IX). It doesn't matter if the company is an asset-intensive business and the most critical metrics are uptime and reliability, or a product-centric manufacturer where quality and efficiency are most critical. If the organization doesn't manage these things holistically, it will lose ground to competitors.
Read MoreCategories: Industrial Transformation / Digital Transformation, IT/OT, Operational Architecture, Asset Performance Management (APM), Factory of the Future
What’s the Difference Between BI and Industrial Analytics?
Posted by Vivek Murugesan on Wed, Apr 03, 2019
During a discussion on industrial analytics at a recent Smart Factory conference in Columbus, Ohio, an IT professional in the audience said that he planned to upload his machine data to online analytical processing (OLAP) cubes and run Business Intelligence (BI) applications on top of the data. The analytics professionals on stage appeared horrified for a moment and went to great lengths to explain the distinction between industrial analytics and BI.
Read MoreCategories: Industrial Internet of Things (IIoT)
Converting Data to Decisions: Why IIoT Technology Alone Isn’t Enough
Posted by Vivek Murugesan on Thu, Jan 31, 2019
The manufacturing industry has had a reputation for being late on technology adoption ever since the steam engines brought the first industrial revolution forward. Even today, while the consumer market has seen the likes of Uber, NeXT, and Spotify leverage latest technologies like Big Data, machine learning, and sentiment analysis to provide products with cutting-edge technology, the manufacturing industry is several steps behind. Even among the manufacturers who are ahead in the technology adoption curve, a good percentage of them have had trouble scaling pilot projects into financially successful projects across the organization.
Read MoreCategories: Industrial Internet of Things (IIoT)
Data Collection in an IIoT-Based MOM World
Posted by Vivek Murugesan on Fri, Dec 14, 2018
Until recently, manufacturing operations management (MOM) software and Industrial Internet of Things (IIoT) platforms were two distinct solutions serving different purposes and providing separate capabilities. That’s no longer the case. MOM software vendors today embed several IIoT capabilities that enable the applications to run at any level in the operational structure. This new degree of connectivity, together with smart connected devices and inexpensive sensors have enabled manufacturers to replace older, monolithic MOM solutions with IIoT-based MOM applications in the plant.
Read MoreCategories: Manufacturing Operations Management (MOM), Cloud, Industrial Internet of Things (IIoT)
Smart Manufacturing Experience 2018: IIoT, VR/AR, 3D Printing, and Whatnot
Posted by Vivek Murugesan on Fri, Jun 08, 2018
The Smart Manufacturing Experience launched its first edition of manufacturing event on April 30, 2018 at the Boston Convention Center. The 3-day event, which focused mostly on Smart Manufacturing, the Industrial Internet of Things (IIoT), additive manufacturing, and augmented reality/virtual reality (AR/VR), witnessed several hundred presenters and attendees from an assortment of companies including IIoT Platform start-ups, industrial analytics providers, 3D printing companies, and big technology players like Microsoft, PTC, among others.
Read MoreCategories: Cloud, Industrial Internet of Things (IIoT), Industrial Transformation / Digital Transformation, Industry 4.0 / Smart Manufacturing, Artificial Intelligence / Machine Learning (AI/ML)
Quality Leaders Explain How Customer Complaints Work for Them
Posted by Vivek Murugesan on Thu, Nov 09, 2017
Quality leaders often view customer complaints as a reactive metric and the last line of defense in their arsenal. Though the term may seem pessimistic on a first glance, when collected, analyzed, and promptly handled, customer complaints have the potential to be a net positive for manufacturers. Not only from a metrics and operations standpoint but also in enabling closed-loop processes and driving a culture of quality throughout the organization.
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Read MoreCategories: Enterprise Quality Management System (EQMS), Cost of Quality (CoQ)