scholarly journals Production Innovation and Effective Dissemination of Information for Operator 4.0

2020 ◽  
Author(s):  
Dan Li ◽  
Åsa Fast-Berglund ◽  
Dan Paulin
Keyword(s):  
Mass Production ◽  
Industry 4.0 ◽  
Manufacturing Industry ◽  
Shop Floor ◽  
Process Innovations ◽  
Product Innovations ◽  
Effective Dissemination ◽  
Everyday Work ◽  
Cognitive Automation ◽  
Organizational Innovations

The manufacturing industry is becoming increasingly more complex as the paradigm of mass-production moves, via mass-customization, towards personalized production and Industry 4.0. This increased complexity in the production system also makes everyday work for shop-floor operators more complex. To take advantage of this complexity, shop-floor operators need to be properly supported in order to perform their important work. The shop-floor operators in this future complex manufacturing industry, the Operator 4.0, need to be supported with the implementation of new cognitive automation solutions. These automation solutions, together with the innovativeness of new processes and organizations will increase the competitiveness of the manufacturing industry. This paper discusses three different aspects of production innovation in the context of the needs and preferences of information for Operator 4.0. Conclusively, product innovations can be applied in the manufacturing processes, and thus becoming process innovations, but the implementation of such innovations require organizational innovations.

scholarly journals Next Generation Industrial IoT Digitalization for Traceability in Metal Manufacturing Industry: A Case Study of Industry 4.0

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 628
Author(s):  
Michail J. Beliatis ◽  
Kasper Jensen ◽  
Lars Ellegaard ◽  
Annabeth Aagaard ◽  
Mirko Presser
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Industry ◽  
Careful Consideration ◽  
Added Value ◽  
Shop Floor ◽  
Circuit Boards ◽  
Next Generation ◽  
Road Map ◽  
Industrial Iot ◽  
Production Cycles

This paper investigates digital traceability technologies taking careful consideration of the company’s needs to improve the traceability of products at the production of GPV Group as well as the efficiency and added value in their production cycles. GPV is primarily an electronics manufacturing service company (EMS) that manufactures electronic circuit boards, in addition to big metal products at their mechanics manufacturing sites. The company aims to embrace the next generation IoT technologies such as digital traceability in their internal supply chain at manufacturing sites in order to stay compatible with the Industry 4.0 requirements. In this paper, the capabilities of suitable digital traceability technologies are screened together with the actual GPV needs to determine if deployment of such technologies would benefit GPV shop floor operations and can solve the issues they face due to a lack of traceability. The traceability term refers to tracking the geolocation of products throughout the manufacturing steps and how that functionality can foster further optimization of the manufacturing processes. The paper focuses on comparing different IoT technologies and analyze their positive and negative attributes to identify a suitable technological solution for product traceability in the metal manufacturing industry. Finally, the paper proposes a suitable implementation road map for GPV, which can also be adopted from other metal manufacturing industries to deploy Industry 4.0 traceability at shop floor level.

scholarly journals FASTEN IIoT: An Open Real-Time Platform for Vertical, Horizontal and End-To-End Integration

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5499
Author(s):  
Felipe S. Costa ◽  
Silvia M. Nassar ◽  
Sergio Gusmeroli ◽  
Ralph Schultz ◽  
André G. S. Conceição ◽  
...  
Keyword(s):  
Real Time ◽  
Industry 4.0 ◽  
Manufacturing Industry ◽  
Business Models ◽  
Production Systems ◽  
Transformation Process ◽  
Digital Transformation ◽  
Shop Floor ◽  
Decentralized Decision Making ◽  
End To End

The Industry 4.0 paradigm, since its initial conception in Germany in 2011, has extended its scope and adoption to a broader set of technologies. It is being considered as the most vital mechanism in the production systems lifecycle. It is the key element in the digital transformation of manufacturing industry all over the world. This scenario imposes a set of major unprecedented challenges which require to be overcome. In order to enable integration in horizontal, vertical, and end-to-end formats, one of the most critical aspects of this digital transformation process consists of effectively coupling digital integrated service/products business models with additive manufacturing processes. This integration is based upon advanced AI-based tools for decentralized decision-making and for secure and trusted data sharing in the global value. This paper presents the FASTEN IIoT Platform, which targets to provide a flexible, configurable, and open solution. The platform acts as an interface between the shop floor and the industry 4.0 advanced applications and solutions. Examples of these efforts comprise management, forecasting, optimization, and simulation, by harmonizing the heterogeneous characteristics of the data sources involved while meeting real-time requirements.

scholarly journals Development of a Smart Cyber-Physical Manufacturing System in the Industry 4.0 Context

2019 ◽  
Vol 9 (16) ◽  
pp. 3325 ◽  
Author(s):  
Tran ◽  
Park ◽  
Nguyen ◽  
Hoang
Keyword(s):  
Radio Frequency Identification ◽  
Mass Production ◽  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Shop Floor ◽  
Self Healing ◽  
Manufacturing Environment ◽  
Information And Communication ◽  
Ict Infrastructure

The complexity and dynamic of the manufacturing environment are growing due to the changes of manufacturing demand from mass production to mass customization that require variable product types, small lot sizes, and a short lead-time to market. Currently, the automatic manufacturing systems are suitable for mass production. To cope with the changes of the manufacturing environment, the paper proposes the model and technologies for developing a smart cyber-physical manufacturing system (Smart-CPMS). The transformation of the actual manufacturing systems to the Smart-CPMS is considered as the next generation of manufacturing development in Industry 4.0. The Smart-CPMS has advanced characteristics inspired from biology such as self-organization, self-diagnosis, and self-healing. These characteristics ensure that the Smart-CPMS is able to adapt with continuously changing manufacturing requirements. The model of Smart-CPMS is inherited from the organization of living systems in biology and nature. Consequently, in the Smart-CPMS, each resource on the shop floor such as machines, robots, transporters, and so on, is an autonomous entity, namely a cyber-physical system (CPS) which is equipped with cognitive capabilities such as perception, reasoning, learning, and cooperation. The Smart-CPMS adapts to the changes of manufacturing environment by the interaction among CPSs without external intervention. The CPS implementation uses the cognitive agent technology. Internet of things (IoT) with wireless networks, radio frequency identification (RFID), and sensor networks are used as information and communication technology (ICT) infrastructure for carrying out the Smart-CPMS.

scholarly journals An Artificial Intelligence-Based Collaboration Approach in Industrial IoT Manufacturing: Key Concepts, Architectural Extensions and Potential Applications

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5480 ◽  
Author(s):  
Panagiotis Trakadas ◽  
Pieter Simoens ◽  
Panagiotis Gkonis ◽  
Lambros Sarakis ◽  
Angelos Angelopoulos ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Business Intelligence ◽  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Shop Floor ◽  
Efficient Production ◽  
Human In The Loop ◽  
Industrial Iot ◽  
Potential Applications

The digitization of manufacturing industry has led to leaner and more efficient production, under the Industry 4.0 concept. Nowadays, datasets collected from shop floor assets and information technology (IT) systems are used in data-driven analytics efforts to support more informed business intelligence decisions. However, these results are currently only used in isolated and dispersed parts of the production process. At the same time, full integration of artificial intelligence (AI) in all parts of manufacturing systems is currently lacking. In this context, the goal of this manuscript is to present a more holistic integration of AI by promoting collaboration. To this end, collaboration is understood as a multi-dimensional conceptual term that covers all important enablers for AI adoption in manufacturing contexts and is promoted in terms of business intelligence optimization, human-in-the-loop and secure federation across manufacturing sites. To address these challenges, the proposed architectural approach builds on three technical pillars: (1) components that extend the functionality of the existing layers in the Reference Architectural Model for Industry 4.0; (2) definition of new layers for collaboration by means of human-in-the-loop and federation; (3) security concerns with AI-powered mechanisms. In addition, system implementation aspects are discussed and potential applications in industrial environments, as well as business impacts, are presented.

Innovation Effects of Science-Related Technological Opportunities / Innovationseffekte von technologischen Möglichkeiten aus dem Wissenschaftsbereich

2005 ◽  
Vol 225 (2) ◽  
Author(s):  
Wolfgang Becker ◽  
Jürgen Peters
Keyword(s):  
Manufacturing Industry ◽  
Innovation Process ◽  
Knowledge Resources ◽  
Process Innovations ◽  
Product Innovations ◽  
Scientific Institutions ◽  
Innovation Output ◽  
The One ◽  
Technological Opportunities ◽  
Theoretical Considerations

SummaryThis paper investigates the innovation effects of science-related technological opportunities. Against the background of theoretical considerations about the interrelation of innovation process and adaptation of external (knowledge) resources, the impacts of technological opportunities stemming from scientific institutions on firms’ innovation input and output are empirically analyzed for the German manufacturing industry. The investigations focus on the question of whether science-related technological opportunities are used as complements or substitutes in the innovation process.The estimations indicate complementary relationships between firms’ innovation input and technological opportunities stemming from scientific institutions. The adaptation of science-related knowledge resources has stimulating effects on the intensity of in-house R&D. The results for the innovation output effects are ambiguous. On the one hand, empirical evidence for complementary impacts on the realization of process innovations could be found. On the other hand, science-related technological opportunities have no enhancing effects on the probability of realizing product innovations. Obviously, knowledge from universities and research institutes stimulates the development of new products more indirectly by increasing in-house capacities and enhancing R&D efficiency.

scholarly journals INNOVATION DEVELOPMENT OF THE FURNITURE INDUSTRY IN BULGARIA

2019 ◽  
Vol 7 ◽  
Author(s):  
Radostina Popova
Keyword(s):  
Innovation Activity ◽  
Furniture Industry ◽  
Innovation Development ◽  
Process Innovations ◽  
Innovation Activities ◽  
Product Innovations ◽  
Innovative Products ◽  
Comparability Of Results ◽  
Organizational Innovations ◽  
The Eu

This paper presents an analysis of the innovation performance of furniture enterprises in Bulgaria for two periods – before the economic crisis and after it. It contains general characteristics of the Furniture industry (structure of the enterprises, different type of production, export and import) and the results of the surveys of the innovation activity for two 3 year periods. The results from the studies are of the periods: 2006-2008 (563 enterprises) and 2014-2016 (358 enterprises) and are based on officially used EU definitions and indicators (European Commission, OECD, Oslo Manual), which allows for comparability of results. The used indicators are: introduced product innovations, introduced process innovations, introduced organizational innovations, introduced marketing innovations, revenues and costs of innovation and financing of the innovation activities. The results of the comparative analyses of the innovation activity of the furniture enterprises in Bulgaria for the two periods under review showed an increase in: the innovation expenditures and revenues from innovative products, the process innovations -  additional  activities and the financing of innovation activities by the EU. It also showed a decrease in the number of furniture enterprises, product innovations, process innovations and organizational innovations.

Employment Effects of Technological and Organizational Innovations: Evidence Based on Linked Firm-Level Data for Austria

2015 ◽  
Vol 235 (3) ◽  
Author(s):  
Martin Falk
Keyword(s):  
Employment Growth ◽  
Negative Impact ◽  
Labour Productivity ◽  
Service Firms ◽  
Demand Model ◽  
Community Innovation Survey ◽  
Process Innovations ◽  
Product Innovations ◽  
The Impact ◽  
Organizational Innovations

SummaryThis paper investigates the impact of technological and organizational innovations on subsequent employment growth using a standard labour demand model. The main novelty of the paper is the use of a unique dataset, which merges the Community Innovation Survey (CIS) 2006 for Austria with structural business statistics from 2006-2008, resulting in 3,070 firm observations. For manufacturing firms, quantile regressions show that product innovations lagged two-years have a significantly positive but decreasing impact on employment growth over the conditional distribution given the impact of output and wage growth. For service firms, the positive employment effect of product innovations can only be observed for firms with high conditional employment growth rates. Results are robust with respect to the measurement of product innovations (e.g. market novelties or new to firm products). Process innovations exhibit a negative impact at the higher quantiles indicating that process innovations lead to an increase in labour productivity at the expense of employment. Furthermore organizational and marketing innovations do not have a significant impact on subsequent employment growth across the different quantiles.

scholarly journals Effects of product and process innovations on the employment growth rate: Evidence for the Colombian manufacturing industry.

2021 ◽  
Author(s):  
Fernando Barrios Aguirre ◽  
Sandra Yaneth Mora Malagón
Keyword(s):  
Growth Rate ◽  
Manufacturing Industry ◽  
Employment Growth ◽  
Technological Development ◽  
Jel Classification ◽  
Firm Level ◽  
Process Innovations ◽  
Product Innovations ◽  
Product And Process ◽  
Positive Effect

Abstract This paper estimates the effect of product and process innovation on the employment growth rate in Colombian manufacturing industry between 2007 and 2012. Based on the model forward put by Harrison et al. (2008), employment growth rate is explained by both the introduction of process innovations that have an effect on old products and the product innovations that have a positive effect on the growth of sales. This research uses the firm-level data panel from the Technological Development and Innovation Survey (EDIT) and the Annual Manufacturing Survey (EAM) in Colombia between 2007 and 2012. Given the firm´s production, results show a positive effect of product innovations on the employment growth rate and a negative effect of process innovations on the employment growth rate in manufacturing firms in Colombia.JEL classification: O25, E24, O33

A Highly Efficient and Optimised Simulation Based Multi objective Decision-Making for FMS Control

2018 ◽  
Vol 6 (6) ◽  
pp. 98
Author(s):  
Shreyanshu Parhi ◽  
S. C. Srivastava
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Manufacturing Industry ◽  
Simulation Software ◽  
Shop Floor ◽  
Simulation Tool ◽  
Routing Flexibility ◽  
Decision System ◽  
Multi Objective ◽  
Arena Simulation

Optimized and efficient decision-making systems is the burning topic of research in modern manufacturing industry. The aforesaid statement is validated by the fact that the limitations of traditional decision-making system compresses the length and breadth of multi-objective decision-system application in FMS.  The bright area of FMS with more complexity in control and reduced simpler configuration plays a vital role in decision-making domain. The decision-making process consists of various activities such as collection of data from shop floor; appealing the decision-making activity; evaluation of alternatives and finally execution of best decisions. While studying and identifying a suitable decision-making approach the key critical factors such as decision automation levels, routing flexibility levels and control strategies are also considered. This paper investigates the cordial relation between the system ideality and process response time with various prospective of decision-making approaches responsible for shop-floor control of FMS. These cases are implemented to a real-time FMS problem and it is solved using ARENA simulation tool. ARENA is a simulation software that is used to calculate the industrial problems by creating a virtual shop floor environment. This proposed topology is being validated in real time solution of FMS problems with and without implementation of decision system in ARENA simulation tool. The real-time FMS problem is considered under the case of full routing flexibility. Finally, the comparative analysis of the results is done graphically and conclusion is drawn.

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