ISE Magazine Volume : 50 Number: 12
By Bublu Thakur-Weigold
Revolutionary customer solutions transform c-part supplier into a valued partner
Bossard AG supplies fasteners – nuts, bolts, screws – to some of the most sophisticated companies in the world. It delivers fasteners to industries ranging from electric vehicles to aerospace, farm equipment and power transmission to precision medical devices and more, with a customer base that includes the ABBs, Siemens, Alstoms, Bombardiers and John Deeres of the world.
The journey began with its SmartBin vendor-managed inventory system and has progressed, as described below, to looking into its customer factories to improve internal logistics and material flows. With a broad portfolio of solutions now called Proven Productivity, this self-described “startup with 185 years of history,” has progressively withdrawn from competing on price only. Its value proposition is to provide the right information at the right place and the right time so manufacturing teams can make better decisions.
Finding solutions at your customers’ site
The sequel to the SmartBin began when Bossard’s engineers realized there was a potential for improving the last mile that fasteners travel on their way to the assembly line. Although most suppliers do not look beyond their customers’ goods receipt ramp, it became clear customers could improve their picking and refilling of material.
The typical factory layout includes a storage area for inbound material, the “supermarket,” whose contents are distributed to bins located close to the assembly line or production cells. There is always a more or less formal factory logistics system, using two bins or kanban, plus a sequence of manual steps. The “water spider” is the worker who tops up materials and components as they are depleted by production, walking erratically between warehouse, supermarket and points of use (comparable to the movement of a spider on a pond).
This person has to return and type the latest changes – depletion of parts, the shift of a storage location – into the enterprise resource planning (ERP) system, which later issues a pick list and identifying labels for the water spider’s next outbound run.
It is easy to grasp the importance of installing the right fastener into a jet engine, medical device or cable car. Yet even in ordinary consumer products – think of the brewing unit of a coffee machine – the wrong screw can lead to dangerous dysfunction. Here was an opportunity for improving manufacturing productivity for customers, along with quality and safety for the end user.
Following up on this insight would require a new intercompany process that would make its customers’ in-house materials handling the business of the supplier. Bossard realized the data it maintained on fastener stock could be combined with details of where each part was stored and the layout of the shop floor to compute how best to reach the point of use. Time, effort and errors could be reduced by optimizing the path of the water spider with paperless instructions in real time. Companies automating their processes in Industry 4.0 programs could later reduce their manual work significantly by integrating robots into the process.
Any changes in bin location and part number could be automated and integrated into the Bossard system, which would have an interface to the customer’s ERP system. With this, Smart Factory Logistics was born, comprising Smart- Bin, SmartLabel and an app-based factory layout program that optimized the internal logistics of the shop floor.
Workers on the shop floor use the app as they walk around to find the bins they are targeting. They are enabled to change or update the information on a part (its description, its location, its reorder parameters) on the spot without having to return to a terminal and log into another program.
Data makes for better c-part management
The trend of Industry 4.0 is to do more with that data. As Urs Güttinger, pioneer of the original SmartBin system and the company’s chief technology officer, recalled: “Five years ago it was good enough to have the screws there when they were needed. Since around 2016, Industry 4.0 initiatives from around the world have now motivated our customers to ask us for more data. We not only provided the statistics of their operations, we are opening our databases so they can download their usage, orders and more.”
Bossard’s customer websites are provided with customized dashboards that display inventory levels, usage and details of individual items, including the status of changes initiated by staff. Electronic SmartLabels display photos of the bins’ contents: Article number, reorder status and date the goods are expected to arrive. With this, manufacturing teams get the right information at the right time at the place where it is needed – and in time to take action. A purchasing or production manager in Europe can look into what was happening at a factory in Asia at the click of a mouse or a tip of a finger on the smartphone.
Driven by their age-old “startup” culture, the engineers in the small town of Zug are not stopping at the Smart- Factory, but looking for new ways to turn their store of operations data into business intelligence for their customers. The future will include predictive analytics based on machine learning algorithms. This will not only compute optimal reorder quantities based on the daily usage patterns from the Smart- Bins, but learn from longer periods of consumption history. By incorporating the costs of stockout and express shipments into the algorithm, their customers can better balance networking capital with higher service levels.
Preliminary tests indicate a further reduction of stockouts at pilot sites. The same data is being used to generate better forecasts than what customers themselves are capable of generating or willing to produce. Artificial intelligence helps predict what is needed on the shop floor based on inputs of production plans, which could eliminate the need to forecast c-parts entirely.
Smiling for profits
The Bossard story illustrates how, with some ingenuity, the smile curve could be reconfigured. It is possible to introduce well-paid knowledge work to the low value manufacturing adds in the sagging middle. It suggests that, even in a global market with low-cost competitors, not every small supplier is doomed to compete on price only in a race to the bottom. Nor do multinational buyers always define all the processes and the division of labor in the supply chain.
When the supplier expands a solution portfolio to include business intelligence, it enables its customers to concentrate on their core competencies, which are usually not c-part management but building cars and other devices. By optimizing the linkages in global value chains, even a small player can break out of the downward spiral of commoditization and create a win-win situation with its partners.
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