Assemble prefilled syringes — plunger rod insertion and cap/needle-shield seating
GSK fills and finishes prefilled syringes (PFS) for vaccines and injectables, a process that requires inserting plunger rods into glass barrels, seating tip caps/needle shields, and handling nested syringes without damaging the barrel or compromising sterility. The components are small, rigid, dimensionally tight parts where the plunger must be driven to a controlled depth without over-pressurizing or cracking the glass barrel, and caps must fully engage to maintain closure integrity. This task occurs at the sterile end of the line, downstream of fill and upstream of inspection and packaging, in a low-tolerance regulated environment. It is difficult for a robot because both insertion force and engagement confirmation depend on force/contact feedback rather than vision, and the glass barrel is fragile. We identified this through our own research; we have not confirmed the specifics with the customer directly. This page is our researched read — a starting point for that conversation.
What the task is
RESEARCHED · our reconstructionGSK fills and finishes prefilled syringes (PFS) for vaccines and injectables, a process that requires inserting plunger rods into glass barrels, seating tip caps/needle shields, and handling nested syringes without damaging the barrel or compromising sterility. The components are small, rigid, dimensionally tight parts where the plunger must be driven to a controlled depth without over-pressurizing or cracking the glass barrel, and caps must fully engage to maintain closure integrity. This task occurs at the sterile end of the line, downstream of fill and upstream of inspection and packaging, in a low-tolerance regulated environment. It is difficult for a robot because both insertion force and engagement confirmation depend on force/contact feedback rather than vision, and the glass barrel is fragile.
Is this the actual task and sequence? What are the real tolerances, cycle rate, and reject criteria, and which steps are today's manual bottleneck? Answering these is what turns this from a researched signal into a validated use case.