TICK Stack: The Open source solution for managing sensor data

Step Zero of your IIoT Analytics journey Applications of IoT in Supply Chain and manufacturing¬† are evolving from hype to maturity and considering the pace of technology explosion, industrial scale IoT solutions become the norm in next 2-3 years in my opinion. You need to get on the learning curve now and start experimenting, if…

Applying Classification algorithms on sensor data for Fault Detection

Introduction One of the numerous advantages of Smart Factories is the real time visibility into operating parameters of your equipments on the floor, transmitted by sensors. Leveraging this data optimally is key to harvesting true benefits from your Smart manufacturing investment. In this post, we will discuss how we can apply Machine Learning methodologies on…

ISA 95 – The Analytics enabler framework behind Smart Manufacturing

Why this sudden interest in Smart Manufacturing? With emerging technologies like IoT and IIoT grabbing headlines, the interest in Smart manufacturing¬† or “The factory of the future” has peaked. Many providers have developed and launched products and platforms that allows manufacturing organizations to convert their manufacturing floors into smart factories (sample representation below). So what…

Leveraging IoT to build a Predictive Logistics platform : An Introduction

Introduction IoT technologies are predicted to generate a massive amount of data, when leveraged at an Industrial scale in Supply Chains. Using IoT technology to gain competitive advantage is actually not just about the data but more about how you leverage all that data being collected. Advanced in technology and computing now allow you to…

Three realistic applications of Clustering algorithms in Logistics Management

In this post, we will explore some applications of clustering algorithms within Logistics Management space that can actually be applied relatively easily and are actually already being used by many organizations. For those who want to try building these models in Python, please email me on singhkum@umich.edu and I can share the Python code and…

Where did Sears go wrong ? A Supply Chain and Analytics perspective

I. Data, data everywhere…not a single byte put to use As you may have read in the Fortune article (link at the end), Sears started as a catalog-only retailer decades before it opened its first store. It got rid of the catalog business in 1993 since it became extremely unprofitable (Sears was supposedly losing $1M/day)….