Mass personalization strategy under Industrial Internet of Things: A case study on furniture production

2021 ◽  
Vol 50 ◽  
pp. 101439
Author(s):  
Jia Ding ◽  
Maolin Wang ◽  
Xiong Zeng ◽  
Wenjie Qu ◽  
Vassilios S. Vassiliadis
Keyword(s):  
Internet Of Things ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Mass Personalization

How Can Industrial Internet of Things (IIoT) Improve Enterprise Productivity?

2020 ◽  
pp. 112-133
Author(s):  
Erdinç Koç
Keyword(s):  
Internet Of Things ◽  
Smart Cities ◽  
Detailed Knowledge ◽  
Healthcare Industry ◽  
Industrial Internet Of Things ◽  
Time Consumption ◽  
Industrial Internet ◽  
Smart Cars ◽  
Industrial Part

This chapter gives brief information about internet of things (IoT) and then detailed knowledge of industrial internet of things (IIoT). Internet of things applications can be seen in different areas, such as smart cars, smart homes, smart cities, agriculture, healthcare, industry, etc. This study focuses on the industrial part. Industrial internet of things (IIoT) means internet of things (IoT) applications for industrial usage. IIoT give a chance to enterprise for tracking supply chains, monitoring production line operations, and real-time consumption of energy, managing stock, and transportation decisions. This study used case study method for developing theory about IIoT's contribution to enterprise productivity. IIoT applications can be adapted to which operations of the enterprise, and how it will contribute to enterprise productivity is explained in this chapter. The chapter discusses the projects that are within the vision of IIoT but not yet implemented and concludes with suggestions for future studies.

Scaling an Internet of Things start-up: Can alliance strategy help?

2021 ◽  
pp. 204388692098616
Author(s):  
Dipankar Chakrabarti ◽  
Soumya Sarkar ◽  
Arindam Mukherjee
Keyword(s):  
Internet Of Things ◽  
Ad Hoc ◽  
Scale Up ◽  
High Tech ◽  
Industrial Internet Of Things ◽  
Start Up ◽  
Industrial Internet ◽  
Multiple Challenges ◽  
Proper Strategy

Owners of start-ups in the high-tech field face multiple challenges while scaling-up. The major challenge is to form a proper strategy that guides them to move from building products for point solutions to more industry-focused solutions, retaining skilled resources, efficient workforce management, and improving market reach. This case study is on Distronix, a start-up in the Industrial Internet of Things that could see steady revenue within 3 years of its operations. Distronix wanted to reach the next orbit fast. Distronix wanted to change the organizational blueprint with a proper strategy to scale-up. The young entrepreneurs owning Distronix brainstormed with their employees and the industry experts to strategize the next phase of growth. Market reach and coping with the changing demand of customers on Industrial Internet of Things were the two most important aspects of their strategy. After discussing with stakeholders and the mentors, the owners focused on alliances to increase their delivery and market reach capabilities. They could establish strong alliances, even with larger companies, with proper planning and sustained quality delivery. From the inception of Distronix, owners established alliance, but those were ad hoc and not as per the holistic plan, which provided them a better focus and guidance on alliancing. The alliance strategy seems successful from its revenue growth but needs regular review as the technology stack is getting refreshed fast. Regular monitoring of performance is also critical. The case study shows the importance of a well-thought and well-rounded alliance strategy for a start-up to scale-up confidently.

scholarly journals Key role and potential of Industrial Internet of Things (IIoT) in modern production monitoring applications

2019 ◽  
Vol 252 ◽  
pp. 09003
Author(s):  
Jakub Pizoń ◽  
Grzegorz Kłosowski ◽  
Jerzy Lipski
Keyword(s):  
Internet Of Things ◽  
Production Management ◽  
Industrial Applications ◽  
Production Environment ◽  
Industrial Internet Of Things ◽  
Time Production ◽  
Industrial Internet ◽  
Monitoring Applications ◽  
Production Monitoring

The following paper presents a key role and potential of Industrial Internet of Things (IIoT) in industrial applications as a solution for monitoring and maintaining manufacturing assets. IIoT is particularly important due to progressing computerisation of hardware resources leading to development of a virtualised model of autonomous real-time production management. Adequately article presents case study of IIoT use in production environment – both methodical and analytic approach is presented.

Semantically-enhanced rule-based diagnostics for industrial Internet of Things: The SDRL language and case study for Siemens trains and turbines

2019 ◽  
Vol 56 ◽  
pp. 11-29 ◽  
Author(s):  
Evgeny Kharlamov ◽  
Gulnar Mehdi ◽  
Ognjen Savković ◽  
Guohui Xiao ◽  
Elem Güzel Kalaycı ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Industrial Internet Of Things ◽  
Rule Based ◽  
Industrial Internet ◽  
Semantically Enhanced

Industrial Internet of things at work: a case study analysis in robotic-aided environmental monitoring

2017 ◽  
Vol 7 (5) ◽  
pp. 155-162 ◽  
Author(s):  
Vito Scilimati ◽  
Antonio Petitti ◽  
Pietro Boccadoro ◽  
Roberto Colella ◽  
Donato Di Paola ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Environmental Monitoring ◽  
Study Analysis ◽  
Industrial Internet Of Things ◽  
Case Study Analysis ◽  
Industrial Internet

Order Fulfilment Progress Estimation for Collaborative Manufacturing Enabled by Industrial Internet of Things

2020 ◽  
Author(s):  
Chen Peng ◽  
Zheng Zhang ◽  
Tao Peng ◽  
Renzhong Tang ◽  
Xiaoliang Zhao
Keyword(s):  
Internet Of Things ◽  
Order Fulfillment ◽  
Manufacturing Companies ◽  
Industrial Internet Of Things ◽  
Production Chain ◽  
Collaborative Manufacturing ◽  
Make To Order ◽  
Industrial Internet ◽  
Order Fulfilment

Abstract It has been recognized by manufacturing companies that working collaboratively is the way to advance their competiveness. Order fulfillment estimation addresses the issue of uncertainty from vendors. It is significant for collaborative manufacturing, which enhances companies’ responsiveness to market dynamics. In a data-rich scenario, order fulfillment estimation can be performed based on information extracted from data acquisition devices, such as smart sensors. The analysis result should serve the decisions-making of the production planning, and an indicator should be passed along the production chain even to its end customer for collaborative purpose. In the meanwhile, the manufacturer’s sensitive or confidential information is excluded to avoid risks. This article studies a method to effectively evaluate the order fulfillment process in an Industrial Internet of Things (IIoT) facilitated make-to-order production system. An order fulfilment progress (OFP) indicator is proposed to dynamically represent the fulfillment progress, and its estimation mathematical models are proposed. To improve the practicability of the OFP indicator in production, the influence of abnormal event scenarios are discussed to modify the OFP. A case study presented in this research demonstrates the proposed indicator with consideration of job in process (JIP) is promising comparing to conventional indicators that are represented by the proportion of finished over total products.

An Integrated Legacy of Modbus Devices to Industrial Internet of Things: Approach for Smart Industries

2020 ◽  
Author(s):  
Karthik Muthineni
Keyword(s):  
Internet Of Things ◽  
Industrial Revolution ◽  
Digital Technologies ◽  
Industrial Internet Of Things ◽  
Intelligent Decision Making ◽  
Internet Of Everything ◽  
Industrial Internet ◽  
Intelligent Decision ◽  
Network Platform ◽  
Smart Factories

The new industrial revolution Industry 4.0, connecting manufacturing process with digital technologies that can communicate, analyze, and use information for intelligent decision making includes Industrial Internet of Things (IIoT) to help manufactures and consumers for efficient controlling and monitoring. This work presents the design and implementation of an IIoT ecosystem for smart factories. The design is based on Siemens Simatic IoT2040, an intelligent industrial gateway that is connected to modbus sensors publishing data onto Network Platform for Internet of Everything (NETPIE). The design demonstrates the capabilities of Simatic IoT2040 by taking Python, Node-Red, and Mosca into account that works simultaneously on the device.

MONITORING AND PREDICTIVE ANALYTICS OF TECHNOLOGICAL EQUIPMENT ON THE BASED OF INDUSTRIAL INTERNET OF THINGS

2020 ◽  
pp. 7-12
Author(s):  
С.Л. Добрынин ◽  
В.Л. Бурковский
Keyword(s):  
Internet Of Things ◽  
Data Acquisition ◽  
Predictive Analytics ◽  
Actual State ◽  
Monitoring And Control ◽  
Industrial Internet Of Things ◽  
Machining Time ◽  
Industrial Internet ◽  
Acquisition Device ◽  
Data Acquisition Device

Произведен обзор технологий в рамках концепции четвертой промышленной революции, рассмотрены примеры реализации новых моделей управления технологическими процессами на базе промышленного интернета вещей. Описано техническое устройство основных подсистем системы мониторинга и контроля, служащей для повышения осведомленности о фактическом состоянии производственных ресурсов в особенности станков и аддитивного оборудования в режиме реального времени. Архитектура предлагаемой системы состоит из устройства сбора данных (УСД), реализующего быстрый и эффективный сбор данных от станков и шлюза, передающего ликвидную часть информации в облачное хранилище для дальнейшей обработки и анализа. Передача данных выполняется на двух уровнях: локально в цехе, с использованием беспроводной сенсорной сети (WSN) на базе стека протоколов ZigBee от устройства сбора данных к шлюзам и от шлюзов в облако с использованием интернет-протоколов. Разработан алгоритм инициализации протоколов связи между устройством сбора данных и шлюзом, а также алгоритм выявления неисправностей в сети. Расчет фактического времени обработки станочных подсистем позволяет более эффективно планировать профилактическое обслуживание вместо того, чтобы выполнять задачи обслуживания в фиксированные интервалы без учета времени использования оборудования We carried out a review of technologies within the framework of the concept of the fourth industrial revolution; we considered examples of the implementation of new models of process control based on the industrial Internet of things. We described the technical structure of the main subsystems of the monitoring and control system to increase awareness of the actual state of production resources in particular machine tools and additive equipment in real time. The architecture of the proposed system consists of a data acquisition device (DAD) that implements fast and efficient data collection from machines and a gateway that transfers the liquid part of information to the cloud storage for further processing and analysis. We carried out the data transmission at two levels, locally in the workshop, using a wireless sensor network (WSN) based on ZigBee protocol stack from the data acquisition device to the gateways and from the gateways to the cloud using Internet protocols. An algorithm was developed for initializing communication protocols between a data acquisition device and a gateway, as well as an algorithm for detecting network malfunctions. Calculating the actual machining time of machine subsystems allows us to more efficiently scheduling preventive maintenance rather than performing maintenance tasks at fixed intervals without considering equipment usage

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