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From the Archives highlights articles from NCTM’s legacy journals, previously discussed by the MTLT Journal Club.

Preparing required data for training object recognition algorithms represents a complex and time-consuming process, that must be avoided especially in industrial environments. The work presented in this paper aims to overcome this challenge through on-line machine learning algorithms, as foundation for further developments and validation. The concept and the developed and validated methodology rely on point clouds resulted from the image processing using a depth camera. The geometry and coordinates of the objects are derived from the point clouds, fact that enables the automation of data preprocessing steps (e.g. manually take the pictures, labelling images), optimizing logistics and production activities.

In manual assembly processes, the information flows during the process are becoming increasingly complex. Digital assistance systems will play an important role in the future by supporting employees and cooperating with them in order to increase productivity, ergonomics, and flexibility. Digital assistance systems must be designed in such a way that they optimally support the abilities of the employees in an adaptive manner. This paper presents an approach to systematically analyze assembly processes with the focus on employee needs and experiences based on Customer Journey Mapping. This approach helps Industrial Engineers to design productive and accepted digital assistance systems for smart factories.

Our working world is on the threshold of a new era: The digital transformation of entire economic sectors and occupational profiles as well as the introduction of new forms of human-machine collaboration through the increased use of big data and cognitive systems require completely new approaches. The key to success in coping with this change, which can be seen in all industries, is to break up old structures and venture something new. The ability to adapt and innovate is becoming a central success-critical factor in entrepreneurial activity. In order to continue to achieve market success and ensure sustainable growth in an extremely dynamic and disruptive environment, enterprises and organisations are called upon to proactively shape change. In addition to the establishment of flexible working models and agile processes, the increased generation and integration of knowledge into and around technical systems in the course of targeted competence development of employees is indispensable. The introduction and use of technical systems thus must go hand in hand with the flexibilisation of innovation and collaboration processes as well as the development of employee skills in order to generate the currently missing socio-technological link – for companies´ added value and for the benefit of people. In this paper, the authors present an overview of currently used creativity techniques and innovation methods and work out the promising potentials as well as basic restrictions of the respective tools. Furthermore, the resulting need for action for the optimisation and enhancement of innovation processes in the interaction of established techniques and possibilities of cognitive systems is presented.

The planning and optimization of human-centered workplaces requires new methodology, which allows the integration of Exoskeletons as a new manufacturing resource or working tool for overcome enormous ergonomics problems when manipulating heavy parts or working over the head. The paper presents the first steps in developing an innovative approach for planning and optimization of smart workplaces with integrated adaptive Exoskeleton. The addressed theme harmonizes three main research areas: a) production technologies and holistic planning of manufacturing processes; b) ergonomics, safety and security of workers in manufacturing environments and c) the component-based configuration of the new type of wearable robotics, Exoskeletons.

The Digital Twins of product and production face the challenge that once the development process is closed, they does not reflect the real status of production where events as equipment failures, poor quality or missing compound parts happens continuously. For assuring production resilience a holistic methodology, combining a top-down with a bottom-up 3D scanning approach for capturing real-time production parameters and embedding them in Digital Twins is developed. The paper presents the methodology and a motivation scenario for further validation in an innovative set-up of an automated measurement cell, where state-of-the-at technologies as autonomous AGV, mobile 3D laser scanning and automated processes are integrated.

Workers are key enablers of flexibility and productivity in Manufacturing, especially in processes where full automation is not feasible. Such workplaces are often characterized by manual manipulation of heavy loads, hazardous conditions and high level of vibrations. Exoskeletons, fusing flexibility, intelligence and human-centered control with the high payload, endurance, precision and sensor-based guidance represent enabling technologies to cope this challenge. In this paper critical parameters for the evaluation of exoskeleton-centered workplaces are identified, as core elements of the methodology for evaluating the exoskeleton-centered workplaces. Comprehensive modelling, simulation and analysis of ergonomics and process parameters represent the foundations of the methodology.

The Exoskeleton represents a promising technology to equip manufacturing workplaces characterized by poor ergonomics, safety and security. Before this technology can be experimented and employed in operational manufacturing environments, the benefits should be highlighted in digital world at the holistic, process, workplace, line and production area levels, with focus on human work conditions. The development of the Digital Twins of Exoskeleton-centered workplaces faces the challenge of approaching the manual assembly and logistics processes as performed by hybrid resources: workers wearing Exoskeletons. From here, the coupling of an Exoskeleton to the digital worker and the realization of the Exoskeleton-Worker Digital Twin requires a thorough understanding of the human models and of wearable robotics, especially Exoskeleton design principles. A coupling methodology was developed and the prototype of the Digital Twins coupled with a commercial Exoskeleton was validated in automotive and logistics industries. The paper presents the performed research for: a) the optimization of the coupling process; b) the modification of the simulation parameters; and c) the embedding of the active Exoskeleton controller to a production and ergonomic simulation software.

The Exoskeleton represents a promising technology aiming to improve physical and organizational ergonomics in manufacturing reducing the physical fatigue, thus enhancing cognitive ergonomics. The foundations of digital transformation of human-centred workplaces with integrated Exoskeletons have been well researched by the group, coping currently with the challenge of optimizing the ergonomics simulation parameters and embedding the Exoskeleton controller in simulation systems. A methodology of capturing in real-time workers' physiological status wearing active and passive Exoskeletons, data interpretation and aggregation towards developing a hybrid human/Exoskeleton Digital Model represents the current work of the group. The performed experiments developed model and validation in several use cases for assembly and logistics activities are reported.

The agile product innovation method Lean Startup Approach is used by startups to quickly adapt to the fast changing market conditions and customer needs. The authors carried out a preliminary study which showed that global challenges such as digital transformation are urging companies to become more dynamic and flexible, and that this method is already used by large companies to meet the needs. Based on the preliminary study, the authors conducted in-depth interviews with experts to examine the procedure for introducing the Lean Startup Approach in large manufacturing companies, and examined the feasibility of applying the method to SMEs..

The Digital Transformation and Industry 4.0 change production work in a holistic and disruptive nature. Most industrial challenges highlight technological aspects since Industry 4.0 is emphasizing on beyond the frontier technology. They revealed the need for organizational changes as well as influences on the human factor. For instance, the employment of assistance systems to support workers on the shop floor allow new information flows by overcoming existing barriers such as hierarchy or distances. Thus, there are not only technological but also more comprehensive implications on work induced by identified use cases. This paper presents few implemented use cases in which technologies optimize or enable new organizational facets to pave the way for new forms of work organization. Building on these use cases, superordinate work organization design principles are discussed.

The employment of intelligent tools in production, such as the new area of wearable robotics, the Exoskeletons, represents valuable and promising technology to reduce the physical stress and increase innovation, productivity and workplace safety. The challenge of realizing these advanced manufacturing environments with integrated Exoskeletons is represented by missing design and planning methods required to equip future workplaces with this enabling technology. The integration of Exoskeletons in logistics and production activities creates a new hybrid type of workstation that has to be designed according to a scientific approach. The article presents the first steps in developing an innovative approach to planning and optimizing intelligent working environments with integrated adaptive Exoskeletons. The topic harmonizes three main areas of research: a) production technologies and holistic planning of production processes; b) ergonomics, safety and security of workers in production environments and c) configuration based on the components of the new type of wearable robotics, the Exoskeletons. The validation of this approach is provided through the creation of digital human/Exoskeleton models combining digital Exoskeleton with various digital human models. The Digital Twin of the human/Exoskeleton system is the heart of a holistic design and optimization process that aims to assess the appropriateness of the selected Exoskeleton by simulating the tasks performed and adapting the simulation parameters. An exemplary validation case in one of the most innovative and dynamic sector, the construction sector, demonstrates the applicability of the model. A guideline for migrate the model in other industry sectors is provided, as well.

Global competition, rapid market changes and the need for more and faster innovations lead to a new risk situation for manufacturing companies. As dynamics increase due to the Digital Transformation, the reliability of success forecasts decreases and many of the product design innovations launched on the market fail. Manufacturing companies, which design products down to the last detail and then develop them over a long period of time and with high investments are highly likely to find that their product will not be accepted on the market. To reduce this risk, agile processes and iterative product design is useful. This approach is based on multiple, iterative tests with customers and the possibility of implementing the knowledge gained. It is important to constantly check, whether the products meet the demand of the market and to design the product in such a variable way, that changes can be taken up immediately and learning effects can be implemented. The Lean-Startup approach is based on these principles. It has been established as a way of thinking for startups and young High-Tech companies who want to optimize their initial market approach through iterative testing of prototypes and continuous improvement through learning. However, the Lean-Startup approach is also suitable for larger companies, which want to make their product development more agile and flexible. This enables companies to react more flexibel to external influences, such as market competition, technologies and politics and to integrate customer needs are more effectively into the product design process. This constant monitoring of the product market fit reduces the risk of developing past the market. This paper introduces an approach for migrating the Lean-Startup approach to large manufacturing companies.

Due to highly competitive markets, constantly shifting consumer requirements, and technological advances, product families are continuously evolving over time. This product evolution leads to new part variants being added to the existing part mix. When at a future time the manufacturing system is not capable, as is or in a reconFigured state, to manufacture the evolved part variants, then this has negative consequences on business performance. This phenomena is being termed as disruptive product evolution. Due to complex interdependencies, incomplete information and uncertainty in manufacturing requirements this phenomena leads to a wicked problem. In order to tame such a wicked problem, this paper contributes and evaluates a knowledge-based decision-making approach that supports manufacturing system designers in exploring the interplay between business strategy, evolving product range and manufacturing systems. A prototype digital factory tool based on this approach has been developed and evaluated. The encouraging results obtained have shown that this research paves the way for the development and integration of such knowledge-based decision-making approaches within state of the art digital factory tools.

The rapid development of digital technologies leads to dramatic changes of our economies and societies – and these are quite far-reaching. Technological progress especially in the field of artificial intelligence (AI) and robotics, big data and business analytics, as well as augmented and virtual reality are providing a total digital connectivity and new possibilities for effective data analysis and handling. Enterprises expect higher productivity and opportunities for optimized performance by increasing use and integration of innovative technologies. Not only machines or intelligent algorithms are going to execute tasks, but new forms of human-machine interaction represent valuable enablers for positioning the central role of humans in design and development activities. In this paper, the authors present an overview of currently available technological solutions in the field of AI leading to new forms of human-machine interaction. Furthermore, functionalities of these technologies and development needs for generating ideas in early innovation processes are identified. The results of this first study build the basis for the next step aiming at mapping the analysed systems with current creativity techniques and methods for optimisation of the innovation process.

The European manufacturing sectors have to face the challenge of workplace safety and security representing costs up to 4% of GNP. A user-friendly and cooperative human-robotic exoskeleton for manual handling work can represent a possible innovative solution. For highlighting and revealing the benefits of human-robotic exoskeleton, represented by increased employment and productivity and reduced back injuries, the validation of this concept in digital and virtual environment has been performed, in two relevant industry sectors, car disassembly and automotive suppliers. The digital models of the test cases and the simulation of ergonomic workplaces were realized by using state-of-the-art Digital Manufacturing technologies and systems. This simulation technology allowed the realization of two states of factory environment, the “as-is” state without an exoskeleton and the to-be state after employing the use of an exoskeleton. The challenges of coupling the exoskeleton to the human operators in Digital Manufacturing Systems, the first results and the next steps, are presented as well.

The employment of Exoskeletons for manual handling work in manufacturing industries aims at increased employment, productivity, safety and security at workplace. This paper highlights several challenges, current results and future steps of our work in optimization of Exoskeleton-based factory environments. “JackEx” is the enhancement of the standard digital humanoid “Jack” with concepts and elements of passive Exoskeletons. For the development of JackEx, a new digital manufacturing resource, the intimate coupling of the Exoskeleton digital model to the humanoid “Jack” components was realized. First the CAD model of the Exoskeleton was decomposed in its elementary compound parts, by creating its corresponding kinematic model. As the next step, the coupling of Exoskeleton digital models to the humanoid was a real challenge since the humanoid and Exoskeleton kinematics are heterogeneous and autonomous. In order to define a common kinematic model of humanoid with integrated Exoskeleton, complex calculus and tests were performed resulting in a new kinematic model. JackEx was deeper validated in a virtual and digital environment through real test cases simulations. The comparison between the simulation results with those performed for the same task but without integrated Exoskeleton, revealed from an ergonomically perspective the benefits of employing the Exoskeleton in manufacturing factories.

Product development has to increasingly handle challenges such as highly competitive market scenarios and rapidly changing customer demands. The Industry 4.0 paradigm has brought about a new range of methods and technologies which can support industry in dealing with these challenges. This paper contributes a digital manufacturing model which aims to support industry to bridge the gap with this advanced digital technologies and foster integrated product development. This digital model achieves this aim by providing a means to illustrate how these technologies can be employed during the different phases of the factory life cycle. The digital manufacturing model also illustrates the soft and meta-skills which need to be developed in order to support digitisation of product development activities. A number of use cases are presented which explore how Industry 4.0 technologies can be implemented within an integrated product development environment.

Exoskeletons aim to improve workplace conditions in industry. The main objective is to optimize actual ergonomic situations. Additional expected positive benefits are to raise quality, flexibility and productivity. There are many attributes, depending on workplace and environmental conditions that have to be considered for the integration and employment of Exoskeletons in production. The requirements of Exoskeletons, a definition and the adjustments for smart and adaptive Exoskeletons will be presented in this paper. The new method ExoMatch presented here is an innovative approach to combine the complex context of workplaces and Exoskeletons in a schematic and process-related line of action. The aim is to support the decision of finding the most suitable Exoskeleton for different working situations, to close the scientific gap by filling the previous manual and personal-depending approach with a novel procedural objective, and a flexible automated approach. To structure all important attributes, a pre-assessment procedure, ExoScore and a preselection-method, ExoMatch of the most suitable Exoskeleton, there is a need of managing all available Exoskeletons and the specific workplaces (ExoData and UseCaseData). The conclusions are followed by an outlook of future work and required methods for planning, assess, objectify and migrate the Exoskeletons in industry.

Background Allogeneic hematopoietic stem cell (allo-HSC) transplantation is used in the treatment of malignant hematological diseases. An important tool in monitoring post-transplantation evolution is represented by the percentage of donor's blood cells found in recipient's blood, known as chimersim. This is useful in predicting the graft rejection and the risk of disease relapse. In this study, we present the importance of multiplex STR markers in chimerism monitoring of a 8 year old girl diagnosed with acute lymphoblastic leukemia (ALL). Methods In the pre-transplant stage, saliva on buccal swabs and blood samples in EDTA were collected from the donor and recipient and used as reference samples. The DNA extraction from saliva and blood samples was done using the Pure Link Genomic DNA kit (Invitrogen, USA). For the DNA quantification, the Quantifiler Human DNA kit (Applied Biosystems, USA) was used on an ABI 7500 Real-time PCR system (Applied Biosystems, USA). Amplification of the STR markers was performed using the AmpFLSTR NGM SElect kit (Applied Biosystems, USA) on a ProFlex PCR System. The PCR products were separated and detected on an ABI 3500 Genetic Analyzer (Applied Biosytems, USA). Results One month post-transplantation of HSC, a mixed chimerism (MC) containing 38% of donor's cells was obtained from a bone marrow aspiration sample. On the 45th day, a new transplantation was performed. On the 15th day after 2nd transplantation, a MC with 91% donor's cells was obtained. On the 21st day after the 2nd transplantation, a complete chimerism (CC) with 100% donor's cells was obtained. Conclusions Chimerism monitoring is useful in identifying those patients in risk for relapse or graft rejection.

Exoskeleton technology is used in manufacturing [1] to support the manipulation of heavy goods in production specific environments. After selecting the most suitable exoskeleton for each specific workstation [2] the next key step includes the optimization of the workplace design and adjustment of exoskeletons according to the workstation’s boundaries, conditions, and constraints. The described impacts with corresponding industry examples and methods should help to understand the influence from these new technology on strategic production objectives, e.g. sustainability, reduced cost, ergonomics, flexibility, quality, and so on. KPIs and their assessment methods are performed at all production scales: beginning from high level for whole production systems, over production processes, production lines and workplace influences, which are particularly used, applied and needed on task-level. Therefore, new exoskeleton based criteria and methods for process planning are discussed intensively. They are used to monitor and especially, to optimize the productions impacts by the planning department and responsible engineers by this presented generic approach. These work present exoskeleton specific impacts define resulting and relevant criteria and corresponding assessments methods. Based on the matching methodology ExoMatch [2] a suitable exoskeleton for the presented example workplace is (pre)selected. With known impacts, the influences and criteria as mentioned before, the novel planning and design approach helps to optimize processes and the workflow by rescheduling and in consideration of suitability, strength and weaknesses of exoskleleton centered workplaces. The content and relevance of this approach is based on experience from industry.

The examination of different sets of sex markers in view of gender determination may seem a routine and yet, no forensic geneticist is exempt from dealing with challenging cases on this issue, even if genetic anomalies related to gender occur rarely. We report a AMEL-Y dropout case revealed on the occasion of a paternity investigation, which proved to be a rare, 46,XX (SRY+) male syndrome, also known as de la Chapelle syndrome. The objective of our case report is to highlight the importance of forensic PCR kits to elucidate anomalies related to gender and overcome the problems related to a wrong genetic gender determination in paternity testing or human identification. The subject is a 36-year-old male requesting a paternity test because he was having doubts related to his 2 year-old child born during his marriage. The standard testing results performed on 16 STRs indicated an exclusion from paternity of our male subject who additionally exhibited an AMEL-Y dropout. We further investigated the male sample using a combination of PCR kits (Y-STRs, X-STRs, Amelogenin and SRY gene) and were able to identify the SRY gene, the loss of the major part of the Y-chromosome, except of a small region surrounding the SRY gene, and the presence of two X-chromosomes. Thus, we finally characterized the AMEL-Y anomaly as being a 46,XX male syndrome. Some basic facts related to the frequency, ethiopathology and diagnosis of this syndrome are reviewed and discussed. This study also represents the first reported Amelogenin dropout case detected in the Romanian population.

In the traditional software development cycle, requirements gathering is considered the most critical phase. Getting the requirements right first time has become a dogma in software engineering because the correction of erroneous or incomplete requirements in later software development phases becomes overly expensive. For product-service systems (PSS), this dogma and standard requirements engineering (RE) approaches are not appropriate because classical RE is considered concluded, once a product service is delivered. For PSS it is impossible to foresee all future context conditions and customization needs customers may come up with after product deployment. In addition, the services supporting a complex hardware-software product depend on the individual product configuration a customer requires. For example, when a standard laser machine is equipped with one or more special sensors, new services may be needed that depend on sensor data from these new sources combined with other data generated by the standard machine configuration. Thus, we claim that RE needs to be extended to the deployment phase of a product and an agile approach is required to cope with emerging hardware and software requirements as a PSS is marketed. In this paper, a novel view-based model-driven engineering approach is proposed that enables collaborative product-service design and customization and copes with evolving, incomplete and unforeseen requirements. A prototype has been implemented as a Proof-of-Concept (PoC) and is currently validated on four industrial pilot cases as part of the H2020 project ICP4Life.

Changing production systems and product requirements can trace their origin in volatile customer behaviour and evolving product requirements. This dynamic nature of customer requirements has been described as a constantly moving target, thus presenting a significant challenge for several aspects of product development. To deal with this constant and sometimes unpredictable product evolution, cyber physical production systems (CPPS) that employ condition monitoring, self-awareness and reconfigurability principles, have to be designed and implemented. This research contributes a CPPS design approach that proactively provides the required CPPS design knowledge. This approach aims to minimise or avoids future consequences and disruptions on the CPPS. This knowledge needs to be provided at the right time whilst not being intrusive to the production system designer's cognitive activity. To effectively deal with the complexity of the cyber physical production system design activity with a manual method would lead to a time consuming, and complex support tool which is hard to implement, and difficult to use. The CPPS design approach has therefore been implemented in a prototype digital factory tool. This paper describes in detail the system requirements and system architecture for this tool. In order to establish the effectiveness of the proposed approach for designing cyber physical production systems, the prototype digital factory tool has been evaluated with a case study and a number of semi-structured interviews with both industrial and scientific stakeholders. The encouraging results obtained from this research evaluation have shown that such an approach for supporting the CPPS design activity makes stakeholders aware of their decision consequences and is useful in practice. This result can lead the way for the development and integration of such knowledge-based decision-making approaches within state-of-the-art digital factory and Computer Aided Engineering Design (CAED) tools.

Failure Mode and Effect Analysis (FMEA) is among the most widely used safety analysis procedures in the various industries. The procedure is generally perceived as complex and time-consuming, hindering an effective reuse of previous knowledge. In this paper we present an innovative usage of knowledge system into FMEA process using the Case-based reasoning to reduce the time and effort associated with this analysis. Knowledge system is built to serve multi-projects work that nowadays are in place in any manufacturing or services provider, and knowledge must be retained and reused at the company level and not only at project level. Collaboration is assured trough web-based GUI that supports multiple users access at any time. Initial results confirm the viability of this system for industrial application.

The implementation of assisted reproduction has increased the incidence of multiple pregnancies. Prenatal death of one fetus in the second trimester of twin pregnancy confronts the obstetrician with a difficult problem with regard to the management of pregnancy. The scarcity of the condition and the absence of the large-scale studies make it difficult to advise the parents on the prognosis and optimal management. The unavoidable birth or death of one premature neonate has led to the aim of delayed interval delivery for the other twin. We present in this report two cases of twin pregnancies with delayed-interval delivery and favorable outcomes for the surviving twins. The twin pregnancies conceived by in vitro fertilization (IVF) in HitMed Medical Center, Craiova, Romania. In the first case, one fetus dismiss in utero at 20 weeks of gestation. The second fetus was successfully delivered by Caesarean section, at 36 weeks. In the second case, the first fetus was delivered at 22 weeks. To save the surviving fetus, ligation of the umbilical cord at the cervical level was performed. The second fetus was delivered at 31 weeks by Caesarean section, in good conditions. We describe our management of the cases and the deliveries and the neonatal outcomes. In multiple gestation, prolongation of pregnancy after preterm dismiss in utero or even after delivery of one fetus is feasible in a closely monitored environment.

In this article, we report a case of pregnancy obtained in an infertile couple diagnosed with severe male factor infertility. The couple attended for fertility examination reporting a history of 10 years of infertility. The cause of infertility was obstructive azoospermia. The treatment consists of in vitro fertilization (IVF). The ovarian stimulation of female patient was done with antagonist protocol and after ovarian puncture was obtained nine oocytes. The urologist performed testicular sperm extraction (TESE). There were selected nine sperm cells by intra-cytoplasmic morphologically selected sperm injection (IMSI). For this purpose, we used an inverted microscope with high magnification equipped with ×60 air objectives with modulation contrast illumination. After intracytoplasmic sperm injection (ICSI) of sperm into the oocytes there were obtained six normal embryos from which three embryos were transferred into the uterus. A singleton pregnancy was achieved which was completed with birth of a healthy baby in time. This successful outcome shows that use of IMSI and ICSI procedures are really useful in selection of best spermatozoa obtained by TESE in treatment of obstructive azoospermia.

Information is one of the key enabler for transformability of factories. As factories have to be able to adapt their processes very fast according to the changing environment, the approach introduced here aims at supporting production process planning and optimization. The performed activities are guided by configuration concepts and methodologies. First the great potential of employing knowledge-based systems in production process planning is emphasized. Afterwards the questions will be answered, what knowledge is relevant, how this knowledge is modeled and how it is used for the configuration of production processes. The contribution closes with a roadmap of future activities.

This paper presents the on-going research steps aiming at the development of a Method for Multi-scale Modeling and Simulation of Assembly System. The focus lies on the Assembly System Base Model and its integration into the whole method. After motivating the research, the developed method and the conceived model of the assembly system is introduced, by using the proposed methodology. The presented approach aims at the manageability of the systems complexity and the acceleration of optimization and adaption processes. It concludes with a roadmap shaping the next steps and activities.

Manufacturing system design is a complex and demanding activity and the system designer has to take many factors into consideration during the development process including the demand and technological requirements of the products or product families. Central to this activity is the synthesis decision making process, during which the designer defines the elements that will make up the manufacturing system. This research identifies in the decision making process a critical activity and contributes a phenomena that can be used by a framework to support designers to address complex issues such as changeability and the evolution of products over the manufacturing system life-cycle., This research work was partially funded through an ERDF Project (Project No. ERDF083). The first and second authors would therefore like to thank the Malta Council for Science and Technology (MCST) who is administering this project., peer-reviewed

The recovery of genetic information from highly degraded or minute amount of biological samples needs special approaches together with conventional STR multiplex assays. In this respect, the "mini-STR" technology is considered to be remarkable for its capacity to decrease the rate of failures and inconclusive results in forensic casework. By using miniSTRs, the PCR efficiency is significantly improved as shorter PCR amplicons are generated with STR primers located closer to the repeat regions. In this article we aimed to present several practical considerations regarding the miniSTR genotyping for challenging forensic samples. Looking for a robust protocol to re-investigate some of our cases with inconclusive or no typing results we studied the efficiency of a miniSTR approach. We report by comparison our results obtained with a commercial miniSTR multiplex assay on samples previously tested with two different 16 STR commercial kits. Our conclusion is definitely in favor of including in the routine protocol the miniSTR assay as it was able to improve the results, providing better or even complete DNA profiles for the difficult samples where the conventional STR kits failed.

Kurzfassung Dieser Beitrag stellt kurz die aktuellen Forschungsaktivitäten des Fraunhofer IPA in Stuttgart im Bereich „Digitale Fabrik“ vor. Theoretische Konzepte für eine durchgängige und kollaborative Fabrik- und Prozessplanung wurden im Rahmen des europäischen Projekt DiFac umgesetzt. Die Beschreibung der konzipierten und entwickelten Architektur der Hauptkomponente Factory Constructor der VR-basier-ten Produktionsumgebung DiFac bildet den Schwerpunkt dieses Artikels.