This study investigates the application of a smart manufacturing execution system (SMES) based on the current controlling structure in a medium-sized company in the Czech Republic. Based on existing approaches on the architecture of SMESs, this paper develops a sample architecture grounded in the current controlling structure of small and medium-sized enterprises (SMEs). While only a few papers on approaches to the given topic exist, this approach makes use of operative production controlling data and uses a standardisation module to provide standardised data. The sample architecture was validated with a case study on a Czech SME. This case study was conducted on two different entities of one production company suggesting differences in the entities due to the nature of production. The research showed that simple tasks with intelligent welding equipment allow for a working SMES architecture, while complex assembly works with a high extent of human labour, and a high number of components still remain an obstacle. This research contributes to gathering more understanding of SMES architectures in SMEs by making use of a standardisation module.

Development of a Smart Manufacturing Execution System Architecture for SMEs: A Czech Case Study

Purpose of the article: The paper focuses on the potentials and benefits controlling provides for companies in the transition period towards industry 4.0. Operative production controlling provides data that shall be used in the future to apply the concept of smart factories. This article proposes a controlling archtitecture based on computer-aided standardization.
Methodology/methods: The paper develops an architecture on operational production controlling based on an international literature review. Literature on controlling 4.0 are found mostly in publications in German language. While this literature has its focus on controlling as a whole or on strategic controlling, the paper has a look on operational controlling and its further usage and development towards smart factories.
Scientific aim: The aim of this article is to develop a model of an operational production controlling architecture that is able to suite the requirements of smart factories by using computer-aided standarization. 
Findings: Research is working on concepts for industry 4.0 and its way towards real implementation. Competitive advantage in industry 4.0 is created through digitization and robotization. An architecture that fully complies to industry 4.0 is still waiting in real companies due to technical limitation in data storing, retrieval and processing as well as storage capacities.
Conclusions: The paper discussed the devlopment of a controlling architecture suitable for industry 4.0. Already today controlling is making use of data. Smart factories shall make use of production data. Production controlling together with the CAS, that is able to provide standardized data on all manufacturing, maintenance, and auxiliary processes, systems are able to make a step forward towards smart factories. The concept of production controlling combined with the strengths of a CAS may be seen as the basis from which to target smart factories and industry 4.0.

https://trends.fbm.vutbr.cz/index.php/trends/article/download/563/195195271

Operative Production Controlling as Entrance into Controlling 4.0

There are many criticisms for the association between the Six Sigma concept and the two statistical metrics associated to 6σ processes: 1.5σ shift for maximum deviation and 3.4 PPM non-conformities for the long-term performance. As a result, the paper aims to carry out an analysis of this problem, and the first result obtained is that a stable process can reach a maximum drift, but its value depends on the volume of the sample. It is also highlighted that, using only the criterion “values outside the control limits” for monitoring stability through the Xbar chart, a minimum value can be calculated for the long-term performance of a process depending on the sample size. The main conclusion resulting from the calculations is that, in the case of a 6σ process, the long-term performance is much better than the established value of 3400 PPB: For small volume samples of two pieces it is below 700 PPB, for three pieces it is below 200 PPB, and for samples with a volume greater than or equal to four pieces the performance already reaches values below 100 PPB! So, the long-term performance of 6σ processes is certainly even better than the known value of 3.4 PPM.

/pdf/the-influence-of-sample-size-on-long-term-performance-of-a-3cvxjuuv.pdf

The Influence of Sample Size on Long-Term Performance of a 6σ Process

Abstract The paper deals with the development and application of computer-aided standardisation (CAS) for the distribution of standardisation data of production and maintenance processes within the company network. Rising integration pressure of company software tools also include CAx technologies. These CAx technologies provide software solutions for different applications, being able to work closely together with ERP-systems, Business Intelligence (BI) tools and further systems. The possibility of integration makes it also feasible to look on the CAS tool and its potential. While CAS is a topic not yet fully discussed, future development may lead to the requirement of integrating the CAS with the ERP and planning system. Approaches, such as CIM, digital factories (DF) and Industry 4.0 benefit from a broader database available with the CAS system employed

Computer-Aided Standardisation for Manufacturing and Maintenance Activities

Six sigma is understood as a technique for the continuous improvement in process quality; however, it has been rarely scientifically analysed in small- and medium-sized enterprises (SMEs). SMEs representthe vast majority of enterprises throughout economies and contribute to automotive supply chains in various tier ranks. As SMEs are known to lack resources and skills while focusing on short-term benefits rather than on long-term gradual improvements, the aim of of this paper is to analyse the perception of six sigma process capabilities in automotive supply chains assuming differences in company size, supply chain rank and six sigma duration. This was tested with Fisher’s exact test. Companies with less than 1000 employees, subsuppliers and companies with a six sigma implementation in the last 3 years struggled to meet six sigma principles, suggesting that mainly small companies inhibit a risk for the supply chain. These findings contribute to the existing theoretical body of knowledge by identifying a three-to-five-year period for six sigma implementations until six sigma maturity. Practically, the findings contribute to the research by explaining the need for a continuous supplier development over a three-to-five-year period until the company meets its performance requirements, with a supply chain risk incorporated in lower-tier ranks and with small companies.

/pdf/smes-in-automotive-supply-chains-a-survey-on-six-sigma-2o08vun5.pdf

SMEs in Automotive Supply Chains: A Survey on Six Sigma Performance Perceptions of Czech Supply Chain Members

This study investigates the changes in team composition in four academic high-tech start-ups and spin-offs. These companies were initiated on academic grounds and had to undergo transition in order to act as private companies. For human resources of all kinds this goes along with a change in the requirements of their skills and their work. This pilot study focused on four high-tech start-ups from Germany and Slovakia that are active and still in transition in the year 2021. Data was obtained with qualitative research methods from managers that were in charge during the transition of the company. During expert interviews, the researchers used semi-structured questionnaires in order to gather data from the managers on particular aspects of spin-off team member skills and requirements. The qualitative results obtained from the managers were compared, showing that with fundamental changes in the business objectives of the company the required management skills and team composition changes from an academic skills portfolio towards a private-sector portfolio. Likewise, a change in the human resource hiring strategy of the spin-offs was found in that stage. However, research also showed that spin-offs seem to undergo two transition phases during their way from an academic research group towards a company based on free market principles.

/pdf/human-resources-in-start-ups-expert-interviews-with-managers-15nek99q.pdf

Human Resources in Start-Ups: Expert Interviews with Managers on the Transition of Start-Ups from Academic to Private

Abstract The paper deals with the direct application of Rapid Prototyping technologies for parts and spare parts production in production companies and the economic effect by making use of this technology. Traditional production technologies are technologies such as forging, cutting, machining, etc. These technologies are widely accepted and the teething troubles are solved. Rapid Prototyping technologies such as 3D printing on the other hand came into the focus in the recent years when the technologies and the produced quality gradually advanced. Providing flexibility and time efficiency the technology should also have a practical application in production. This paper has the aim to provide a case-study based on existing cost figures to show that these technologies are not limited to prototype developments.

Rapid Prototyping Technologies for Manufacturing and Maintenance Activities

Purpose of the article During the COVID-19 pandemic in the years 2020 and 2021, supply chains have been heavily affected and disrupted. With the lack of material and the lack of available containers for oversea shipment, a further upcoming issue where the exploding oversea container transport prices.

Marcel Rolf Pfeifer

Papers

Computer-Aided Standardisation for Manufacturing and Maintenance Activities

SMEs in Automotive Supply Chains: A Survey on Six Sigma Performance Perceptions of Czech Supply Chain Members

Human Resources in Start-Ups: Expert Interviews with Managers on the Transition of Start-Ups from Academic to Private

Rapid Prototyping Technologies for Manufacturing and Maintenance Activities

Supply Chains Strategies during COVID-19: Green Supply Chain vs. Supply Chain Sustainability