Why Industry 4.0?
According to a survey by the American Society for Quality (ASQ) in 2014, 82% of organizations who have implemented smart manufacturing claimed to have experienced increased efficiency, “49 % reported fewer product defects and 45 % experienced increased customer satisfaction” . Based on a survey conducted among major manufacturing giants in 2013, the Intelligence Unit of “The Economist” reported 95% of the respondents would like to see IoT as a part of their manufacturing process by 2017..
What is Industry 4.0?
The German Federal Ministry of Education and Research defines Industry 4.0 as “the flexibility that exists in value-creating networks is increased by the application of cyber-physical production systems (CPPS). This enables machines and plants to adapt their behavior to changing orders and operating conditions through self-optimization and reconfiguration. The main focus is on the ability of the systems to perceive information, to derive findings from it and to change their behavior accordingly, and to store knowledge gained from experience. Intelligent production systems and processes as well as suitable engineering methods and tools will be a key factor to successfully implement distributed and interconnected production facilities in future “Smart Factories”. Since exchange data and information between different devices and parties in real time is the key element of smart factories, such data could represent production status, energy consumption behavior, material movements, customer orders and feedback, suppliers’ data, etc.
What is OEM 4.0?
OEM 4.0 is a phase of Industry 4.0 which is a major focus of MachineSense. In plain terms, OEM 4.0 is aimed at original equipment manufacturers of various industrial equipment to make that equipment smarter—and help drive value for the customers of the equipment manufacturers as well as improve machine serviceability. Many manufacturers are mechanically oriented with steady improvements in machine features and benefits and have historically relied on outside automation or PLC suppliers for their control systems. However with the MachineSense OEM 4.0 platform, the target is to bring Industry 4.0 and the Industrial Internet of Things (IIOT) benefits to OEM manufacturers quickly, easily and affordably so they will not be left behind as Industry 4.0 progresses. OEM 4.0 is a program to bring equipment manufacturers up to speed with new predictive platforms so they can differentiate themselves quickly and easily. Increasingly, end-use customers will come to expect these predictive sensor/app benefits as a standard offering and Industry 4.0 and OEM 4.0 will be commonplace. Every equipment manufacturer will be expected to offer predictive analytics within a few short years, our programs can make this happen now.
What are the vital features for Industry 4.0? How Is the MachineSense Platform Delivering It?
The most common and vital information needed for Industry 4.0 is predictive maintenance (condition based monitoring), energy usage of each machine, operational utilization, productivity of the machine, reconfiguration of the machine and process, quality control, process monitoring and integrating customer relationship management. The MachineSense platform integrates all of these applications through a cloud engine, Crystal Ball.
1. Predictive Maintenance: Health of the machines is tracked in real time to show how machine health is deteriorating. From the trend line we are also able to predict in how many days/months, the machine will need maintenance or whether is it safe to operate that machine.
The ability to track the process parameter and product quality in real time is one of the stated goals of Industry 4.0
2. Energy Optimization: Tracking energy usage of the process in real time: Energy consumption constitutes up to 25% of the operating cost of any factory. Energy can be wasted in a manufacturing environment for many reasons, prime among them is non-optimized utilization of the machine. For example, a machine can be made to operate for hours even while dormant, waiting for material feed. Thus, when a machine is not producing anything, it is still operating in full load mode, adding unnecessarily to the cost. This is just one of many typical examples of energy waste in industry. With the MachineSense system, such wastage can be tracked and alarmed via email. (Fig 3.0)
3. Process Diagnosis and Tracking: The ability to track the process parameter and product quality in real time is one of the stated goals of Industry 4.0. Conventionally, such data is collected by a PLC and fed to a DAC system. However, process diagnosis needs an analytic engine on top of process data, and it must be real time. The MachineSense Gateway system can be integrated with a PLC and data can be analyzed locally in the data hub itself to deliver a real time diagnosis system for the process. (Fig. 4.0).
4. Machine utilization per unit of productivity: Given a set of operable machines, are you maximizing factory production and thus utilization of the machines? This is the most common issue for most factory managers. They have no automated way of knowing which machine is producing at an optimal level and which machines are not really being used that often for production. For a small factory, such information may be qualitatively understood but for a large manufacturing plant or for a multinational manufacturing company with dozens of facilities all over the world, it is impossible to track productivity and utilization of each machine via a real time and historical time dashboard. The MachineSense system enables such analytics even without the need of PLC coding. (Fig. 5.0)