Nammo (Norway)

No abstract

The digitalization of manufacturing is the essence of Industry 4.0 realization. Many large manufacturers have developed ambitious digitalization strategies, and most have taken the first steps towards digital transformation. Unfortunately, the same cannot be said for small and medium-sized enterprises (SMEs). At the same time, SMEs contribute on average with more than 50% of the value to the economy in the European Union and with almost 100 million employees, represent approximately 70% of the European workforce. This makes the onset of Industry 4.0 and the accompanying digitalization of manufacturing a fundamental challenge for most SMEs, many of which already struggle to remain competitive in a rapidly evolving business climate. As such, in this paper, we aim to present an SME-friendly approach to Industry 4.0 implementation. We share practical insights from three SME case studies that enable us to propose the lean first … then digitalize approach to Industry 4.0 implementation in SMEs.

A shift to a Circular Economy requires more than the implementation of new processes and activities. It also requires identification of new opportunities to create and capture value by analyzing value captured and uncaptured across the product life cycle. However, previous studies focusing on value captured and uncaptured have consistently employed the value uncaptured (VU) framework in isolation. Hence, this study combines the VU framework with extended value stream mapping (EVSM), to identify waste and value improvement opportunities with ‘high’ circularity. Based on an in-depth case study of a firm that produces patient simulators, both approaches have been applied. The findings of the current study prove the effectiveness of integrating EVSM and the VU framework when firms are to evaluate the possibilities for realizing value opportunities for a circular economy.

This paper investigates how lean production levelling methods can be better applied in the process industry with support from key enabling technologies from Industry 4.0. To investigate such a topic, a literature study is conducted in three main areas, namely production planning in the process industry, Lean Production, and Industry 4.0. Based on the findings from the literature review, a conceptual framework is developed to illustrate the ability of Internet of Things, Big Data Analytics, and the further integration of IT systems to provide increased reliability for materials, processes, equipment, and forecasts that improves the utilization of Heijunka (production levelling) practices in the process industry.

Nowadays significant part of plastic and, in particular, thermoplastic products of different sizes is manufactured using injection molding process. Due to the complex nature of changes that thermoplastic materials undergo during different stages of the injection molding process, it is critically important to control parameters that influence final part quality. In addition, injection molding process requires high repeatability due to its wide application for mass-production. As a result, it is necessary to be able to predict the final product quality based on critical process parameters values. The following paper investigates possibility of using Artificial Neural Networks (ANN) and, in particular, Multilayered Perceptron (MLP), as well as Decision Trees, such as J48, to create models for prediction of quality of dog bone specimens manufactured from high density polyethylene. Short theory overview for these two machine learning methods is provided, as well as comparison of obtained models’ quality.

A very compact and rugged 2.5-D integrated data logger has been built and tested. The data logger is capable of measuring accelerations exceeding 70 000 g. Microcontroller and flash memory as bare dies have been mounted onto a silicon interposer with through silicon vias using anisotropic conductive film and Au stud bump bonding. A microelectromechanical system accelerometer is mounted onto the interposer, using a robust customized flip-chip mounting approach. The interposer is mounted into a 16-pin leadless chip carrier package using isotropic conductive adhesive, where the conductive part is made of metallized polymer spheres. The ceramic package was mounted onto an application printed circuit board (PCB) with filters, power management, and an interface contact, using soldered plastic core solder balls (PCSBs). The diameter of the data logger is less than 9 mm, and the height is approximately 5 mm. The data logger fits within 12.7-mm (0.50 cal.) projectile, and acceleration measurements have been performed during firing, flight, and recovery. The measured accelerations have been verified by comparing the calculated projectile muzzle velocities with Doppler radar measurements.

Manufacturing industry has often used different types of quality improvements to reach a "near zero" perfection in product and process development this is often strategic objectives. Manufacturing of products with a large number of components and difficult geometries, often have high probability of detective output products.

Abstract Environmental and health considerations have encouraged the development of ammunition with substitutes for lead and other heavy metals. In general, the emission products from munitions containing nitro‐based propellants are highly complex mixtures of gases, vapors, and solid particles. The major combustion products are H2O, CO, CO2, H2, and N2. In addition, compounds including hydrogen cyanide (HCN), ammonia (NH3), methane (CH4), nitrogen oxides, benzene, acrylonitrile, toluene, furan, aromatic amines, benzopyrene, and various polycyclic aromatic hydrocarbons are detected in minor concentrations. Many of the identified chemical species have severe toxicological properties, and some of the compounds do even have mutagenic effects. Gun smoke emission is a concern because its exposure to humans may be substantial during military and civilian police training, as respiratory protection equipment is not routinely worn. In this work we study the compositions of some of the main decomposition products, experimentally as well as theoretically. The concept of frozen equilibrium at around 1500–2000 K appears to apply for CO, CO2, and H2. However, the trace species in the combustion mixtures appear theoretically to be present in negligible concentrations. Our measured results are many orders of magnitude higher than theoretical results in open space. We forecast that future development of gun powder will focus on reducing the amount of toxic trace species.