Manufacturing Technology

Additive Manufacturing Network platform connects community of design engineers

By Schaeffler, a global automotive and industrial supplier, to connect its community of design engineers with its AM Fab Shop for additive manufacturing to facilitate collaboration, speed time to production and to foster greater application of the benefits of additive manufacturing (AM) within its value-chain. Siemens’ AM Network digitalises the additive manufacturing workflows (order-to-delivery process chain) of customers and partners, as well as applying additive manufacturing on an industrial-grade to scale their business. With the AM Network, customers and partners are enabled to build up their own additive manufacturing ecosystem (company-internally as well as with their trusted external suppliers/partners), and to join the existing ecosystem already established over the past years on the AM Network platform. With demand for additively manufactured parts growing exponentially among its R&D designers and engineers, Schaeffler has adopted Siemens’ AM Network as the single platform for all engineering/ technical collaboration throughout the entire AM order-to-delivery process. This cloud-native platform enables it to take advantage of the benefits of additive manufacturing more quickly, efficiently and at greater rate of scale by digitalising and streamlining additive manufacturing workflows. R&D designers and engineers are guided through the AM part qualification process, as defined by the AM Fab Shop, while shop floor operations and machine utilisation have been streamlined to increase efficiency. Time and effort are saved with increased throughput while fostering a wider understanding of the benefits of additive, better formalisation of best practice and ultimately, more efficient execution and more timely delivery of the successfully 3D printed parts. Siemens‘ Additive Manufacturing Network platform was selected not only to assist orchestrating the end-to-end order-to-delivery process for industrial additive manufacturing, but was perceived as a long-term partner to grow with and to explore further opportunities to create a fully digitised end-to-end AM workflow and value chain. The Additive Manufacturing […]

WebLytics solution for collaborative applications

OnRobot makes its software debut with the launch of WebLytics, a unique production monitoring, device diagnostics, and data analytics solution designed to enhance productivity and minimise downtime. Capable of monitoring the performance of multiple collaborative applications simultaneously and in real-time, WebLytics gathers equipment data from both robots and tools and transforms it into easy-to-understand, visualised device and application-level intelligence. WebLytics provides real-time, application-focused data for collaborative applications across major robot brands. WebLytics marks the beginning of OnRobot’s journey into robot software and completes their vision of providing a One Stop Shop for collaborative applications on both the hardware and software side. For end users and integrators, WebLytics not only eliminates manual data collection — it provides actionable insights into how well a collaborative application is performing, offering live device diagnostics, alerts and preventive maintenance measures to keep costly robot cell downtime to a minimum. Integrating the globally recognised overall equipment effectiveness (OEE) industry standard, WebLytics identifies trends in real-time in the robot cell, including patterns, peaks, and disturbances in application productivity. OEE measures the percentage of manufacturing time that is truly productive – a score of 100% indicates that the collaborative application is producing only good parts, as fast as possible, and with no downtime. Leveraging these OEE measures, WebLytics can determine whether the manufacturing process is running at optimal speed and can monitor and analyse the quality of application cycles –key insights for manufacturers of all sizes. WebLytics can report on utilisation of the robot arm and OnRobot tools such as grippers, vision cameras, and sensors, as well as the number of safety stops initiated, and the number of grip cycles performed while an application is running. When changes are made to a robot cell, such as adjusting the speed of a robot or the settings on a gripper, […]

Australian manufacturer develops cutting edge tool for underwater recovery

The custom recovery jaws will assist HEART with underwater recovery missions. Blueprint Lab, an Australian robotics manufacturer, has developed custom jaws for their Alpha robotic arm which will allow for greater grip on fabric when resurfacing underwater drowning victims. This tool was developed for the Hutterian Emergency Aquatic Rescue Team (HEART). HEART are a volunteer group of certified divers from Manitoba, Canada who specialise in emergency water search, rescue and recovery. Using a combination of highly-skilled human divers and specialised technology, they are able to recover victims of tragic drowning accidents from the waterways of their region, including arctic underwater environments. The HEART operators have been using Blueprint Lab’s Reach Alpha subsea robotic grabber to assist them in recovery missions but were having trouble with the intense grip stability required to resurface deceased victims. They got creative and temporarily installed a makeshift DIY nail modification to their grabber in the short term, and then approached Blueprint Lab for an engineered solution. Blueprint Lab’s engineering team began developing and testing a grabber upgrade that would fulfil these specific task requirements, resulting in a new tool specialised for Search and Recovery – the Reach Alpha Special Recovery Tool. As well as looking the part, the Special Recovery Tool is strong, sturdy, and sharp making it an effective solution for HEART’s requirements. The Blueprint Lab team are thrilled to have worked with HEART to ensure their continued mission success. Always keen to rise to the operational challenges faced by partners and customers no matter how unique or challenging. “Here at HEART Team we use the Blueprint Lab manipulator on our VideoRay Pro 5 ROV for body recoveries. We had an opportunity to speak with the folks from Blueprint Lab about our work and the need for a grabber that is more suitable for […]

Robotic solution to nuclear waste

An innovative robotic solution to mapping and segmenting different levels of nuclear waste without the need to put humans into a hazardous radioactive environment has been proven by a pioneering company. Createc is behind some of the world’s most advanced technologies in robotics and computer imaging and is well-known for finding solutions to some of the world’s most complex industrial challenges. Createc’s Automated Nuclear Detection Cell (AND-C) innovation responds to the challenge of removing nuclear workers from hazardous environments by providing a system that can remotely scan items for radioactive contamination and then automatically remove the contamination. Createc’s technology involves an AND-C sensor pack being deployed on a robotic arm. The sensor scans the contaminated item and the 3D radiation contamination map is transferred directly to the robotic system to guide the arm to the precise location and remove the contamination. The AND-C system allows remote radioactive decontamination without requiring operators to work inside a hazardous nuclear environment. In many nuclear decommissioning facilities, a decontamination cell is used to process transport containers on site so that they can be sentenced to low level waste. This is labour intensive work which needs to be carried out using complex PPE and sometimes air-fed suits and involves multiple operational teams as well as support staff and radiation protection staff. Combining Createc’s proven technology for radiation mapping with nuclear robotic arms means the precise location of the contamination can be identified and removed without having to put nuclear workers into this hazardous environment. It means operations can be carried out more safely, sooner and also at less financial cost. Identifying different levels of nuclear waste in this way will result in significant financial savings as it will mean low level waste will not be sent to intermediate level waste facilities unnecessarily. Createc’s tried and tested N-Visage […]

Marcelo Tarkieltaub Digital transformation PIC

Digital transformation paving the way to recovery in a post-pandemic world

By Marcelo Tarkieltaub, Regional Director, Southeast Asia at Rockwell Automation The pandemic presented new challenges for many industries, including manufacturing. With digitalisation on everybody’s lips, the question is, how can manufacturers best leverage technology, automation and IoT to rebound and future proof their organisations should a similar crisis occur? One of the biggest challenges to impact manufacturers was the restrictions Covid-19 placed on workplace access. With many employees encouraged to work offsite, it resulted in lean engineering and service teams on the factory floor, enterprise risk and limited availability of assets and operations. It left companies tacking a few questions. First, how to ensure an efficient workforce and operations, while protecting employees’ health and safety and conducting training. Second, how to keep their business running efficiently and profitably, maintaining business continuity in the mid to long term in the face of logistics challenges. Last, how to reduce downtime of assets and the need for maintenance while continuing to operate with lean onsite staff. To alleviate these challenges, manufacturers should follow three guiding principles to keep their workforce safe, while preparing for ongoing uncertainty and long-lasting changes to the work environment. Protect the workforce. Standardise operating procedures and tools that keep staff safe, such as implementing regimented social distancing and protective garments on the factory floor, and building workforce confidence through effective, two-way communication that responds to concerns. Manage risks to help to ensure business continuity. Anticipate and be ready to respond to potential changes with speed and agility, as exemplified in the sudden demand for PPEs and masks at the height of the pandemic. Coupled with export limitations from supplier countries, manufacturers had to quickly transition from their regular portfolio and pivot into PPE manufacturing. A flexible factory floor and scenario planning well ahead of the fluctuations enabled manufacturers to […]

Manufacturers can use ‘assets-as-a service’ approach to build better products

By Kevin Dherman, Chief Innovation Officer at SYSPRO Innovations and the evolution of technology has seen a positive shift in how businesses are able to capture data to help them make informed business decisions. In the span of a decade or two, businesses have progressed from the time intensive process of manually gathering data across the business to try to draw a meaningful conclusion from any further examination. The challenge was that a good data conversion seldomly made an impact across the value chain but thankfully, the rise of digitalisation and automation in manufacturing is resulting in the generation of a colossal volume of data. Today, new technologies are connecting the manufacturer directly to their operations and their customers like never before. With historical data as a foundation, manufacturers can fulfill a promise to end customers. They can track inventory anywhere in the supply chain as well as track and forecast delivery dates of raw materials as well as accurately forecast manufacture dates. One way in which manufacturers are collating data at the edge is through the Internet of Things or a network of interconnected sensors, instruments and other devices. Businesses are then able to access a single source of truth through their ERP system and use data insights to facilitate the improvement of productivity and efficiency. While data insights are clearly the route to improved operational efficiencies, the industry is also asking whether there is an opportunity to generate new revenue streams through data monetisation and the re-exploration of business models. Defining data monetisation Gartner defines data monetisation as the process of using data to obtain quantifiable economic benefit. Internal or indirect methods include using data to make measurable business performance improvements and inform decisions. External or direct methods include data sharing to gain beneficial terms or conditions from […]

A humanoid robot with a shopping trolley is shopping at a grocery store. Future concept with robotics and artificial intelligence. 3D rendering

The technologies driving opportunities in automation

Swisslog Australia & New Zealand Managing Director Francis Meier discusses these trends and the future of automation. Fast-moving industries like retail, food and beverage, warehousing, and logistics have been driving the boom and rapid advancement of e-commerce and the digital marketplace. Intralogistics, AI, Digitalisation and IoT are already thrusting industry forward in ways we never would have thought possible in years gone by. “Just as the merging of digital, AI and remote monitoring are hallmarks of Industry 4.0 in industrial markets, these giant steps in automation will be commercial markets’ pathway to the future. Leaders in their field are already moving into these fields, and the benefits are beginning to filter through to new levels of industry,” said Mr Meier. “As these future-focused technologies advance further, automation-driven industries need to ask how they can not only utilize these advances, but actively shape the new technology to deliver specific business advantages, and achieve long-term growth,” he said. Turning big data into big opportunities One of the key themes is big data, and how forward-thinking companies can better utilise this information to drive growth and company advancement. “Big data refers to large and complex data sets being collected and stored continuously. Collection is one part of the equation – how we use it is the more challenging, and exciting part,” says Mr Meier. “With the right tools, such as intelligent software, it is possible to transform big data into ‘smart data’. This is where you can optimise processes, provide clarity on past, present and future operation figures, and be proactive rather than reactive to change.” Companies to benefit from automation growth The continued growth in automated solutions and intelligent use of data will significantly improve warehouse performance, and allow companies to flexibly adapt to change, says Mr Meier. “The Covid-19 pandemic has […]

How distributed manufacturing is reducing operational risk

By Mathew Hunter, innovation product marketing manager, Konica Minolta Distributed localised production has emerged as a counterpoint to globalisation as it places the production of goods closer to consumers or at the point of use. Using additive manufacturing means manufacturers can produce goods onsite, which delivers a host of financial, efficiency, and environmental advantages. Although globalisation can offer businesses many benefits, the trend towards distributed manufacturing is increasing. Particularly in recent times, this acceleration is due to factors such as: rising fuel prices, which has significantly increased long-haul shipping cost; concerns over climate change and its negative environmental effects; and the lack of control over stock levels, timing and import restrictions when relying on overseas supply lines. Distributed manufacturing uses additive manufacturing to place production sites across dispersed locations, which are interconnected and coordinated through technology. Sites can download designs and 3D-print them on the spot. Because this model relies on local manufacturing, producers have a higher level of flexibility and agility, providing faster turnaround times, quicker delivery of goods, and customised products. This can help manufacturers compete more effectively, particularly in a disrupted environment, as it reduces operational risks. By implementing a distributed manufacturing model, manufacturers can overcome many challenges currently impacting global trade, including constant trade wars and tariffs as well as pandemic-related border closures. Setting up local manufacturing operations also helps support innovation for individual manufacturers and helps the country as a whole gain more resource sovereignty. The New Zealand government has recently launched an approach to industry policy to help grow more innovative industries across the nation. Manufacturing is a key industry for New Zealand to grow and become a more productive, sustainable, and inclusive economy. The Advanced Manufacturing Industry Transformation Plan aims to: help lift the sector’s productivity, sustainability, inclusivity, and quality of work; and […]

Schaeffler expands OPTIME availability

The latest update of OPTIME integrates Schaeffler’s condition monitoring systems (CMS) SmartCheck and ProLink. OPTIME therefore covers condition monitoring for a very wide range of machines and often even entire plants. Analysis enables maintenance teams to predict machine problems and act appropriately. As a result, customers reduce downtime and increase the profitability of their machinery. Avoid downtimes, increase profitability Particularly for companies operating in system-intensive process industries, avoiding unplanned downtimes means greater profitability. Via the smartphone or desktop app, customers with OPTIME have a constant eye on the status of their plant, even with hundreds of machines, as the messages are user-friendly and prioritised according to criticality. As a result, in-house maintenance personnel or even service companies can plan maintenance measures, personnel utilisation, and the procurement of replacement parts in a timely and cost-efficient manner. They have the flexibility to decide whether they want to draw on other services and if so, which ones. The modular service concept offers online, remote or on-site services. Condition monitoring can be easy Users of digital services in the industrial environment also expect the information provided to be easily understood and the hardware and software to be uncomplicated to get around. Condition monitoring systems by Schaeffler can be used without needing extra qualifications because with the help of the Schaeffler know-how, the system configuration and data analysis are largely automated. This integrated knowledge is integral not only to the highly scalable OPTIME solution with wireless single-channel sensors, but also to the two systems for machines with dynamic speed and load conditions and involving environments with temperatures in excess of 85 degrees Celsius – the single-channel CMS SmartCheck and the multi-channel CMS ProLink. With condition monitoring solutions, operators and maintenance personnel have an expert eye tracking the condition of practically every machine in the plant […]

Addressing the six biggest losses in manufacturing

-Rob Stummer, APAC CEO,SYSPRO As the manufacturing sector continues to navigate chinks in the global supply chain while trying to meet customer demand in a COVID era of restrictions, the fact remains that manufacturing is an industry that the pandemic has put under the spotlight and one which continues to be more competitive than ever. For manufacturing organisations, the priority remains on reducing waste, being more efficient and continuing to have a competitive edge over others. Being able to identify what is referred to as the six big losses will provide businesses with an equipment-based perspective on lost production time that they can use as part of their improvement program. Some manufacturers have implemented programs like Total Productive Maintenance (TPM) and focused on improving Overall Equipment Effectiveness (OEE) with the aim of streamlining manufacturing processes and increasing output. While TPM is an equipment maintenance model that aims to achieve perfect production with no breakdowns, slow running or any other machine related problem that affects throughput. OEE is a metric that measures how well the machine is being utilised, otherwise known as uptime, the speed of the machine and the quality of the production. In the past, due to legacy Operational Technology (OT) systems, manufacturers had no clear visibility into the manufacturing process and could not always tell where equipment bottlenecks were. OEE supports TPM based initiatives by measuring progress towards the nirvana of perfect production and one of the most effective ways of improving OEE is to identify the six big losses. 1. Equipment failure Equipment defects and failures result in downtime, financial impact, inventory discrepancies and poor quality-control. This situation can occur for several reasons and can be because of unplanned downtime, no available operators and a lack of raw materials. When equipment is scheduled for production but is not running for any significant period due to a failure of some sort, it is categorised as equipment failure and is an availability loss. A simpler way to think of […]

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