Successfully realize Industry 4.0 s potential with accurate forecasts and automated decision-making

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1 Blue Yonder in practice Successfully realize Industry 4.0 s potential with accurate forecasts and automated decision-making Examples of applications of Blue Yonder Predictive Analytics in industry

2 Blue Yonder offers industrial organizations industry-specific forecasting software that enables them to gain valuable knowledge and automate the decision-making processes. This is achieved by using the organizations growing data volumes from advanced sensor networks. Blue Yonder s leading team of data scientists produce accurate forecasts of the highest quality using innovative techniques such as predictive modeling and machine learning. The Blue Yonder project team consists of data scientists and software developers with specialized scientific backgrounds, having gained extensive knowledge in utilizing and processing enormous data volumes (Big Data) at international research institutes such as CERN. We develop solutions for challenging tasks in both business and industrial organizations, based on our vast experience in enterprise software and in Software as a Service (SaaS). We provide our predictive applications in the form of Platform as a Service (PaaS) in the cloud. The machine-learning approach ensures that changing conditions are permanently recognized and included in the analyses, thus enabling us to continuously deliver precise forecasts. 2

3 A view of the future smart industry with predictive analytics Industry 4.0, smart services, and data-driven enterprises are key areas that industrial organizations have to manage today in order to stay ahead of the competition and make use of the efficiency gains through automation. Enormous and sometimes overwhelming data volumes and being able to utilize this data in a sensible way are the main challenges for organizations today. It is the sensible use of data, rather than the mere capability to process data, that will separate tomorrow s market leaders from the stragglers. This brochure will illustrate four use cases describing how Blue Yonder s Predictive Application Platform supports manufacturers and suppliers in successfully mastering both current and future challenges. 3

4 Spare parts logistics and demand planning for the manufacturing industry The challenge The spare parts function is an important area with rising growth rates that contribute significantly to the overall margin of the manufacturers and suppliers. This is true for automotive supply companies, for example. Not to be confused with individual spare part sales, but the optimization of the entire supply chain from the manufacturer to the retailer. Knowing which spare parts and the quantity that need to be shipped to a certain business unit or region at the precise time can be vital in contributing to improved manufacturing and logistics planning. An organization that has a robust and sustainable overview of its exact stock and requirements can improve its service level and simultaneously lower storage costs. On a customer side, the rapid and sustainable delivery method of replacements parts for complex machinery, such as vehicles, ensures continuous operation and heightened customer satisfaction and loyalty. What does Blue Yonder Predictive Analytics do? Accurate and robust forecasting of global spare part needs Automation of supply chain processes, so that the right spare parts are available at the right time to the right customer The added value for enterprises Reliable forecasts lead to a reduction of the reporting/safety stock Reduction of capital costs in the storage facilities Increased service level Increased customer satisfaction 4

5 Remote emergency analysis Improving repair and maintenance services for end customers The challenge The large amount of sensor data that machines, devices, and vehicles are sending and using, opens new possibilities in recognizing patterns and in planning. This of course is providing that the right software is used. And, as is so often the case, time is of the essence. Shorter delivery times and the need to recognize demand for a technician s attention, or receiving spare parts on time, improves workshops and service departments readiness to deliver. What does Blue Yonder Predictive Analytics do? Recognizing patterns in production lines and machines, and predicting errors With Predictive Analytics from Blue Yonder, organizations draw the right conclusions from machine data and vehicle data in order to optimize decision-making processes and to be able to better plan, ahead of time. For example, patterns of a production line can be identified at an early stage, errors can be predicted before they happen, and repairs can be carried out on time which means that maintenance times can be kept. Lowering the costs of recalls Blue Yonder Predictive Analytics can also contribute to cost reductions and more efficient processing regarding potentially expensive recalls. At the right time, an installed chip in the vehicle that has a trained forecasting model recognizes that the vehicle needs a replacement part or a repair. Automate support and maintenance procedures Once Blue Yonder detects a situation that will likely lead to a failure, it can schedule service appointments automatically, enabling detailed error logging to warn the customer about productivity impact. The added value for enterprises On-time availability of spare parts and shorter processing times in the workshop, as well as fewer machine downtimes Improved service for the end customer and the service units Reduction of warehouse costs and logistics costs Protection of the company image 5

6 Condition-based services Individual maintenance based on real maintenance requirements The challenge Organizations that work with service contracts have to continually walk a thin line in calculating and determining conditions, to offer customers the optimal service level they require as well as keep an eye on the profitability of the service at the same time. Every unnecessary increase in maintenance frequency increases total cost of ownership, while an overly harsh decrease can have extremely negative results. For existing service agreements, at a specific time, a decision must be made as to whether they will be extended over the standard term and at the same, or at changed conditions. For equipment and machines, depending on the engine running time and weather conditions, a decision must be made as to whether the contract will be retained at conditions deemed by the customer to be favorable, or be changed. Issues like lump sum contracts and billing for each time the service technician works need to be negotiated. What does Blue Yonder Predictive Analytics do? Data analysis; pattern recognition based on equipment; machine condition; accurate forecasting of risks, stoppages, as well as maintenance demands derived from them Inclusion of external factors such as weather and other environmental influences to more accurately predict the length of the optimal maintenance interval Automation of maintenance schedules, based on predictions gained from sensor data The added value for enterprises Accurate forecasts mean that optimized service contracts can be offered for each individual customer 6

7 Transparency of energy efficiency in production The challenge With rising energy costs for industrial enterprises, energy efficiency has become more important. Energy consumption is an enormous cost factor. Enterprises view entering into favorable contracts as the way to meet the challenge of reducing energy costs and peaks in consumption. What does Blue Yonder Predictive Analytics do? Pattern recognition based on machine data, sensor data, and energy consumption data Recognition of the individual energy drivers within a production facility If relevant, inclusion of external factors in the analysis Precise forecasts on future energy consumption and peaks in consumption Automation of machine operation to avoid energy usage peaks and make maximum use of times of availability of cheap energy The added value for enterprises Detailed knowledge of energy consumption across the individual units of the production facility Identification of the drivers of energy consumption Avoidance of peaks in consumption, for example through delayed facility and machine switching and adjustment of the machine run times Better energy contracts enabled A valid basis for using specific machines 7

8 Do you want to learn more about the use options of predictive analytics in industry? Then please contact us. We would be glad to hear from you. Blue Yonder UK Limited 6-9 The Square Stockley Park Uxbridge UB11 1FW United Kingdom Phone +44 (0) Fax +44 (0) Blue Yonder GmbH Ohiostraße Karlsruhe Germany BY_ Phone +49 (0) Fax +49 (0)

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