Production Planning & Control
Why smart sequencing is becoming a backbone of modern vehicle assembly
Rising product variety is forcing automakers to rethink sequencing strategies to stabilise assembly, protect workers and scale production efficiently.
Sequence formation is no longer purely a logistics issue in many car factories. It determines whether vehicle lines meet their cycle targets, whether material arrives on time at the line, and whether the workload of the teams remains balanced throughout the shift. In practice, the diversity of variants is increasing because combustion and electric vehicles as well as different derivatives run in parallel on common lines. At the same time, parts availability is subject to higher levels of fluctuation. Patrick Ball, responsible for the planning processes of the powertrain plants at Daimler Truck AG in Mannheim, Kassel and Gaggenau, describes the dual role of his organisation as both supplier and customer.
The plants serve customers worldwide and simultaneously time manage suppliers worldwide. Call-off fluctuations and disruptions such as missing parts or inventory discrepancies made sequence formation more difficult. Ball says: "We put a lot of effort into sequencing and then spend the whole day creating an optimal sequence programme." On the OEM side, the challenge becomes visible when several series with very different technology levels are manufactured on one line.
Sequencing under pressure from growing product diversity
Fabian Troll, responsible for control and sequencing at Porsche Leipzig GmbH, reports on three model series being produced on one line and a wide spread in technology. The task is to schedule vehicles in such a way that avoids overloads on the line while maintaining optimal staffing levels. Between a very simple and a maximally scheduled vehicle, the work content can differ by around 50%. To compensate for these differences, the assembly works with mixed scheduling, floating, and specifically deployed jumpers. This support is still often provided on call today, but could become more manageable with digital tools, as overload peaks are predictable in terms of time and space.
Behind the operational effects is often an IT landscape that has developed over time. In the transition to S/4HANA and in the demarcation between ERP, APS, and MES, sequencing is becoming a key topic again. As a result, it is increasingly understood as an interdisciplinary task in which departments and IT must jointly define rules, data, and system boundaries.
We put a lot of effort into sequencing and then spend the whole day creating an optimal sequence programme.
The technical challenge lies in the multitude and interaction of restrictions. In component plants like Daimler Truck, typically 20 to 30 rules apply per aggregate type, including scheduling rules, distance rules, and capacity specifications for personnel deployment. Ball describes the effort behind these rule sets as high and dynamic. Restrictions sometimes arise as a reaction to acute problems and are later revised. Each additional rule increases complexity because a solution must meet as many requirements as possible simultaneously. In Leipzig, the scale is similar. Troll currently mentions around 25 restrictions but points out that rules are interdependent, resulting in significantly more effective combinations.
Why stability matters more than pure efficiency
To assess the sequence quality, Porsche Leipzig relies on the stability of the so-called pearl chain. The sequence is set approximately two weeks before the start of assembly and adjusted again shortly before entering production - typically four hours prior. The target is 95%, meaning that 95 out of 100 planned vehicles run in the intended order. This stability is intended to bring calm to production and logistics, thereby supporting punctuality and quality, as overload at the cycle can promote stress and errors. In terms of worker utilisation, assembly aims for around 90% of the cycle time on average. In component plants, sequence stability is also discussed as a central target metric. Ball refers to it as the master KPI for a target image in which a sequence is planned several days in advance and then checked for compliance. Transparency about why sequences are violated is crucial. A standardised tool should also support the harmonisation of the three component plants and create comparability.
Algorithmics meets shop floor reality
Software providers rely on a combination of mathematical optimisation, heuristics, and adaptive methods in sequencing. Simon Altemeier, managing director and sequencing expert at Taktiq, comes from assembly planning and describes how the view from the shop floor has shaped product development. He has experienced that employees on the line immediately feel different loads and therefore often push early for a better sequence.
Through this practice, the idea emerged to treat sequencing not as a black box, but as a controllable process. Altemeier reports on applications where sequencing tasks that previously required several hours of manual checking could be solved algorithmically in a very short time. He says: "We were really able to sequence something like that flawlessly in 30 seconds." At the same time, Altemeier emphasises that performance alone is not enough.
Equally important is the interface with people. Planners must understand why a solution is created, which rules are violated, and what goal conflicts are behind it. Only then can trust be built, and sequencing be operated stably as part of the production system. In practice, this means mapping weightings and priorities in a comprehensible way. Adherence to deadlines, capacity utilisation, distance and neighbourhood rules, load carrier circulation, block formation rules in painting, or time-related specifications such as special vehicles in a specific shift must be brought together in a model.
From an OEM perspective, the focus is increasingly shifting from rigid restrictions to work-content-based models. Troll describes that sequences today are no longer formed solely according to rule sets, but consciously with cycle times in the background. Work content, paths, and station occupancy are used to simulate the load, over the sequence. This allows restrictions to be reduced in perspective and to control more strongly over real utilisation on the line.
Planning at Porsche Leipzig is now largely automated. The software calculates the pearl chain completely, the employee checks the result and usually adopts it unchanged. Troll also attributes the necessity of this automation to the human factor. With increasing complexity, it became apparent that shifts had different planning styles and employees on the line could recognise who had fed in the sequence. From the plant's point of view, it was therefore necessary to support colleagues systemically.
The challenge is to schedule vehicles with completely different work content so that there is no overload for the workers and we still operate with exactly the right personnel.
Integrating logistics, body shop and final assembly
A central theme is the consistency of the sequence across process chains. In vehicle production, assembly is often scheduled backwards to align paint, body construction, and internal component manufacturing in a common sequence. Troll describes that the paint sequence is generally oriented towards assembly and colour blocks are integrated where possible. At the same time, an attempt is made to start with the same basic rules in body construction so that the logic remains consistent from the body shop to final assembly.
This coupling does limit extreme block strategies, but avoids additional complexity due to constantly changing sequences between areas. In component plants, the situation is similar, but even more driven by throughput due to different lead times. Ball describes a backward scheduling and a spread of lead times from less than a day to five days. To use the output warehouse as a buffer, orders are sometimes deliberately brought forward and sequences are designed so that pre-assembly, main assembly, and material flows fit together. Especially in pre-assembly, there is still little system support today and a lot of manual work, which depends heavily on experience.
I have worked on the line myself and have experienced these different loads. This gave rise to the idea of better controlling the sequence.
Sequencing as an enabler for scalable and automated production
For sequencing to become economically viable on a broad scale, Altemeier cites a pragmatic threshold of at least 15 consecutive stations in a flow system and a noticeable spread in variants and work content. Then, data-based mixed takt planning can help reduce bottlenecks, avoid production losses, and minimise the use of floaters. Applications are not only found in car plants but also in trucks and buses, in the assembly of motorhomes, forklifts, cranes, and agricultural machinery.
The digitalisation of sequencing falls into a phase where the automotive industry is further automating its production systems while also aiming for greater flexibility. Many manufacturers and suppliers are simultaneously examining how humanoid robotics or other new forms of robotics can be integrated into assembly scenarios, such as for material-related tasks, rework, or ergonomically unfavourable steps.Such approaches increase the need for precise takt and sequence planning because humans and robots must coordinate their work within the same takt structures. Sequencing thus becomes a connecting element between planning, logistics, and the shop floor. It is intended not only to optimise the order of tasks but also to create the conditions for factories to simultaneously master scaling, variant mix, and new automation technologies.
