The benefits of industry 4.0 in manufacturing are clear, but unlocking them requires organizations to overcome capacity constraints. The keys are in these change management strategies.
Asset Performance Management software must evolve into knowledge hubs that not only deal with monitoring, but also gathering data from other dependent systems to provide much deeper insights and greater control.
New technologies and processes must have a demonstrable impact on a company's bottom line to make a convincing argument for adoption. In that spirit, here are seven recent manufacturing process improvements and how they affect profits.
Whether it be hybrid, multi, or on-premise, cloud technology has the ability to significantly increase productivity and scale processes throughout the entire organization.
Given the advanced state of anthropogenic climate change and widespread awareness of its human impact, it's time for manufacturing to adopt carbon offsetting practices.
The direct influence of a workforce in determining an organization's purpose can be as much, and, sometimes even more of a reason for an individual to enthusiastically and wholeheartedly work at a company as the financial compensation they receive.
Overall equipment effectiveness (OEE) has been a leading manufacturing performance metric for decades. As Industry 4.0 has taken off, manufacturers now have a range of new tools and techniques that can improve their OEE scores.
With many maintenance operations still planned and performed manually, often by experienced operators performing sometimes basic yet time-consuming tasks, it is easy to see how manufacturers are sometimes swimming against the tide when it comes to achieving efficiency goals.
By addressing some of the most prominent pitfalls, leaders can adopt this growing workplace trend without compromise. Here are three critical challenges to a remote work transition and steps every manufacturing leader can take to mitigate those difficulties today.
A 2020 survey conducted by industrial automation provider Yokogawa revealed that 48 per cent of respondents valued productivity as a key focus in their digitalization strategies, while 40 per cent regarded operational efficiency as their main objective.
As someone who has spent his life engaged in driving growth at every level of business operation, it's always been evident to me that to be successful and meaningful to all stakeholders, a corporation needs positive purpose if it hopes to achieve sustainable profitability.
Today's most sophisticated metrology systems drive quality assurance (QA) which has become a fundamental digital task which in and of itself facilitates efficient and cost-effective production processes.
Artificial intelligence (AI) is one of the fastest-growing technologies in the business world today. AI is a broad umbrella, covering many specific technologies, and machine learning is one of the most promising of these.
Automating the traceability process is essential for manufacturers who want to avoid production bottlenecks, reduce production costs, and improve the marking quality to meet OEM traceability requirements.
Let's face it, evaluating and implementing new technology, especially something as huge and all-encompassing as ERP, is a daunting task. Many of us choose a technology solution that fits our needs now.
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