Operations Article

Lee Seok Hwai’s picture

By: Lee Seok Hwai

Hong Kong scientists teaching a panicked populace to make their own surgical masks with paper towels and metallic wire must surely rank as one of the most Kafkaesque moments of the new coronavirus disease outbreak. But the worst is yet to be if global medical supply chains, already stretched in parts to breaking point, are not shored up to cope with the pandemic.

A desperate shortage of surgical masks, the most visible symbol of the epidemic since China began fighting it at the start of the year, underscores the scale of the problem. The country made five billion masks last year and supplied about half of the global market. But with its people churning through tens of millions of masks every day, China is cranking up domestic production even as it imports medical gear from the West.

Peter Dizikes’s picture

By: Peter Dizikes

Suppose you would like to know mortality rates for women during childbirth, by country, around the world. Where would you look? One option is the WomanStats Project, the website of an academic research effort investigating the links between the security and activities of nation-states, and the security of the women who live in them.

The WomanStats Project, founded in 2001, meets a need by patching together data from around the world. Many countries are indifferent to collecting statistics about women’s lives. But even where countries try harder to gather data, there are clear challenges to arriving at useful numbers—whether it comes to women’s physical security, property rights, and government participation, among many other issues.  

For instance: In some countries, violations of women’s rights may be reported more regularly than in other places. That means a more responsive legal system may create the appearance of greater problems, when it provides relatively more support for women. The WomanStats Project notes many such complications.

Jesse Allred’s picture

By: Jesse Allred

Imagine a manufacturing facility prioritizing cleanliness and organization—aisles are kept clear, equipment is well maintained, the plant floor is regularly cleaned, operators can easily locate tools, and materials are always stored in the right place. All employees contribute to managing work spaces, creating a culture of efficiency and quality.

Sophia Finn’s picture

By: Sophia Finn

Effective and efficient supplier management is possible, but not when we’re still using old tools and expecting different outcomes.

Emailing suppliers to communicate product specs, corrective action requests, or audit reports may be “the way it’s always been done,” but that doesn’t mean it isn’t inefficient and risky. The email black hole is a real thing, and busy quality professionals cannot be expected to remember every supplier correspondence and response. Excel spreadsheets are a favorite for many of us, but how can you ensure data accuracy and accessibility when spreadsheets are stored on someone’s computer or on a shared drive?

When you think about it, using yesterday’s tools to manage suppliers infuses uncertainty, inefficiency, and a lack of traceability and transparency at every step. “The way it’s always been done” introduces a level of risk entirely unnecessary, given the availability of modern, cloud-based supplier quality management solutions.

Jennifer Grant’s picture

By: Jennifer Grant

With Covid-19 continuing to impact many businesses, lead time as well as sourcing new suppliers is increasingly difficult. If you currently outsource manufacturing overseas, it is likely you have encountered some turbulence to your supply chain.

Rapid prototypes and large-quantity production of special precision parts and components are key to many business’s operations. Along with this, an agile business strategy that enables the sourcing of verified suppliers, as well as maintaining production-line efficiency, are critical. With travel to Asia currently stalled, and many factories presently closed or operating at low capacity, this strategy is not easily executed for many companies worldwide. Although engineers have a wide array of companies to choose from to get their machining parts manufactured, the turnaround time can be weeks from order to delivery.

Quality Digest’s picture

By: Quality Digest

This is supposed to be trade-show season. The time when companies send their employees to industry tech shows and user-group meetings to see and experience the latest offerings in their field. A time when companies expend a good portion of their budget on booth space, shipping costs, and hotel and travel expenses to get their products and employees in front of thousands of people.

This year, however, due to concerns about the Covid-19, conferences are being cancelled left and right. From fashion to food to finance, show websites are plastering “cancelled” notices across their home pages. Design News  lists dozens of tech shows around the world that have shuttered or postponed. These include shows from Apple, Facebook, Google, Gartner, and both the China and Korea Semicon shows.

By: John Wenz

For most of us, the word “robot” conjures something like C-3PO—a humanoid creature programmed to interact with flesh-and-blood people in a more or less human way. But the roster of real-world robots is considerably more varied. The list includes Boston Dynamics’ dog-inspired robots, Dalek-like security bots, industrial arms on an assembly line, and any number of flying insect-inspired robots. If a machine is designed to do a complicated task in an automated fashion, it’s a robot.

A robot, it turns out, doesn’t even need to have a fixed shape. That’s the vision of researchers who work in modular reconfigurable robotics (MRR) and are pursuing bots that can assemble themselves, by rearranging similar or identical parts into whatever shape suits the task at hand. These robots can take the form of snakes, lattices, trusses, and more, and can be set to any challenge—providing construction support, doing repair work, or scouring for survivors after a natural disaster.

Knowledge at Wharton’s picture

By: Knowledge at Wharton

Companies and societies are at the precipice of rebuilding their foundations to compete in an age of advanced analytics, artificial intelligence (AI), and machine learning (ML). Yet, in the real economy—or in the world outside the tech companies—I see more struggle than success in making advanced analytics and AI a management discipline.

Most leaders in these companies recognize that the perfect storm of big data, computing capacity, and algorithmic advances has arrived. They hear about spectacular use cases such as AI outperforming trained radiologists in detecting retinopathy in preemies. Research also shows that text analytics of earnings calls reveal that executives’ use of euphemisms (think “headwinds”) obscures the details of bad news and delays negative investor reaction. Yet, many leaders feel unsure about this new environment and are struggling to extract value from these cutting-edge technologies.

Sean Spence’s picture

By: Sean Spence

The outbreak of the Covid-19 virus in China and the railway disruptions across Canada represent two different yet similar classic case studies. They remind us that nations and global economies are becoming increasingly interconnected. Incidents thousands of kilometers away are being felt locally. This is a result of the increasing importance of critical infrastructure (CI).

In order to mitigate these negative consequences to organizations—like lost revenue, lost customers and reputational damage—they must have well-structured and defined contingency plans in place to meet operational objectives.

What’s known as critical infrastructure has many different definitions within academic literature and among different governments worldwide. But essentially, CI can be defined as infrastructure so vital that its incapacity or destruction would have a debilitating impact on the economy or the defense of the country and therefore becomes a national security issue.

Mark Lilly’s picture

By: Mark Lilly

Shop floor scheduling is a huge headache for many manufacturers. You can’t operate without it, but operating with it presents a host of challenges. In particular, scheduling systems struggle to account for the many variables present in a typical high-mix, low-volume shop.

Each of the following common shop-floor scheduling models offers its own drawbacks, often creating one problem as it attempts to solve another. That’s why the solution to better production management isn’t implementing yet another shop floor scheduling system that doesn’t align with your reality—it’s rethinking the approach entirely.

Manual scheduling

Manual shop floor scheduling can take many forms, from a whiteboard on the wall, to an Excel spreadsheet, to a stack of papers with a work order written on each sheet. These manual approaches are cost-effective and easy to implement with little to no learning curve to get off the ground. At the end of the day, the jobs have to get done, and shop floor managers typically turn to manual scheduling because of its low barrier to entry.

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