Johan S. Carlson

Quadratic Sensitivity Analysis of Fixtures and Locating Schemes for Rigid Parts

The main purpose of locating schemes are to position parts. The locating scheme utilizes tooling elements, referred to as locators, to introduce geometric constraints. A rigid part is uniquely positioned when it is brought into contact with the locators. By using kinematic analysis we derive a quadratic sensitivity equation that relates position error in locators with the resulting displacement of the part held by the locating scheme. The sensitivity equation which depends on the locator positions and the workpiece geometry around the contact points can be used for locating scheme evaluation, robust fixture design, tolerancing and diagnosis. The quadratic sensitivity equation derived in this paper is novel by adequate dealing with locator contact at nonprismatic surfaces, nonsmall errors, locator error interaction effects and locator errors in arbitrary directions. Theory for comparing the relative gain in precision by using the quadratic sensitivity equation instead of the linear is developed. The practical relevance of the quadratic sensitivity equation is tested through numerical experiments.

Managing Physical Dependencies through Location System Design

Many geometrical quality problems that arise during production and assembly can be traced back to the way parts are designed and located to each other; that is, how the interface geometry and locating schemes are designed and selected. Today, locating schemes are often generated after the geometry has been set, or as a consequence of the part geometries being designed. In many situations, locating schemes are not deliberately designed or defined at all. This often results in assembly and positioning situations that are not clearly defined, analysed or understood by the designer. Since the way parts are located to each other is critical for how geometrical variation will propagate and cause variation in critical product dimensions, more emphasis should be put on this activity in early design phases in order to avoid assembly and production problems later on. This work proposes a structured top-down procedure for selecting locating systems for parts and subassemblies, and presents design guidelines to assist assembly modelling. The procedure can be seen as a first step in robust design and tolerance analysis in the area of geometry design and assurance. The proposed procedure utilizes an assembly dependency matrix, a locating scheme library, a number of different part-sensitivity analyses and a set of design guidelines.

Assembly Root Cause Analysis: A Way to Reduce Dimensional Variation in Assembled Products

The objective of root cause analysis (RCA) is to make the trouble shooting dimensional error efforts in an assembly plant more efficient and successful by pinpointing the underlying reasons for variation. The result of eliminating or limiting these sources of variation is a real and long term process improvement. Complex products are manufactured in multileveled hierarchical assembly processes using positioning fixtures. A general approach for diagnosing fixture related errors using routine measurement on products, rather than from special measurements on fixtures, is presented. The assembly variation is effectively tracked down into variation in the fixture tooling elements, referred to as locators. In this way, the process engineers can focus on adjusting the locators affected by most variation. However, depending on the assembly process configuration, inspection strategy, and the type of locator error, it can be impossible to completely sort out the variation caused by an individual locator. The reason for this is that faults in different locators can cause identical dimensional deviation in the inspection station. Conditions guaranteeing diagnosability are derived by considering multiple uncoupled locator faults, in contrast to previous research focusing on single or multiple coupled locator faults. Furthermore, even if an assembly is not diagnosable, it is still possible to gain information for diagnosis by using a novel approach to find an interval for each locator containing the true underlying locator variation. In this way, some locators can be excluded from further analysis, some can be picked out for adjustment, and others remain as potential reason for assembly variation. Another way around the problem of diagnosability is to make a higher level diagnosis by calculating the amount of variation originating from different assembly stations. Also, a design for diagnosis approach is discussed, where assembly and inspection concepts allowing for root cause analysis are the objective.

Maximizing Smart Factory Systems by Incrementally Updating Point Clouds

Many industry leaders have recognized the need to reinvent the way factories operate. This has led to the Industrie 4.0 and Industrial Internet initiatives, which advocate the use of cyber-physical systems to provide customers with personalized products. The authors present a data-driven approach based on the idea of a digital factory--that is, a virtual representation of production plants and processes that can facilitate virtual analysis. Specifically, the proposed tools can help decision makers assess existing assembly lines for their maximum degree of customization using up-to-date and physically accurate models of their factories. The authors achieve this by maintaining up-to-date information about a factory floor via incremental laser scanning of structural changes. They then combine this with simulation tools to compute maximum design volumes to guarantee collision-free and product-customizable production lines. They also present a case study that examines the reusability of a rust treatment facility for multiple car chassis models at Volvo.

Energy efficient and collision free motion of industrial robots using optimal control

In a production plant for complex assembled products there could be up to several hundred of robots used for handling and joining operations. Thus, improvement in robot motions can have a huge impact on equipment utilization and energy consumption. These are two of the most important aspects of sustainability in a production system. Therefore, this paper presents an algorithm for generating efficient and collision free motion of industrial robots using path planning and direct transcription methods for numerical optimal control. As a measure of efficiency for moving between configurations we use a combination of the energy norm of the applied actuator torques and the cycle time. Velocity and torque limits are handled and modeled as hard constraints. However, more general problems can be solved by the same approach. Our novel algorithm solves the problem in three steps; (i) first a path planning algorithm calculates an initial collision free path, (ii) a convex optimal control problem is then formulated to follow this path, and finally (iii) a nonlinear optimal control problem is solved to iteratively improve the trajectory. The resulting trajectory is guaranteed to be collision free by restrictions in the configuration space based on a local sensitivity analysis. The algorithm has been successfully applied to several industrial cases demonstrating that the proposed method can be used effectively in practical applications.

Coordination of robot paths for cycle time minimization

In this work we study the problem of coordinating robot paths sharing a common environment in order to minimize cycle time, by avoiding their mutual collisions. This problem is particularly relevant in the automotive industry where several robots perform welding operations to assemble and join a car body. The main contributions of this article are: to model the path coordination problem in a graph based way similar to job shop scheduling problem; to solve the path coordination problem by a branch and bound optimization algorithm exploiting the cylindrical structure of the problem. A computational study is presented where the correctness and performance of the new algorithm are evaluated by comparing it with a Mixed Integer Linear Programming formulation, solved by a general purpose package: good results are presented, with computing time differences of even three orders of magnitude. Finally, the algorithm has been interfaced with a state-of-the-art simulation software: within this framework an industrial test case from the automotive industry is solved. A straightforward way to modify pre-computed robot programs, implementing the optimized schedule is also described in pseudo-code. The efficiency of the solver and the robustness of the generated robot programs make the method very appealing in practice.

Root Cause Analysis for Fixtures and Locating Schemes Using Variation Data

This paper proposes a locating scheme method for diagnosis. The method utilises measurements/sensor readings to estimate the variation in contact points between the fixture and the workpiece. Kinematic analysis is used to derive a linear sensitivity equation that relates position error in locators to sensor readings. By using a subspace estimation technique based on the sensitivity equation the sensor variation is separated into noise and locator variation. The root cause of fixture failure is identified by ranking the estimated locator variation. The approach is attractive because it can deal with multiple coupled locator failures and is not limited to a 3-2-1 locating scheme, but works for an arbitrary deterministic locating scheme.

A Generalized Method for Weld Load Balancing in Multi Station Sheet Metal Assembly Lines

Sheet metal assembly is investment intense. Therefore the equipment needs to be efficiently utilized. The balancing of welds has a significant influence on achievable production rate and equipment utilization. Robot line balancing is a complex problem, where each weld is to be assigned to a specific station and robot, such that line cycle time is minimized. Industrial robot line balancing has been manually conducted, based on experience and trial and error rather than mathematical methods. However, recently an automatic method for robot line balancing was proposed by the authors. To reduce robot coordination cycle time losses, this method requires identical reach ability of all line stations. This limits applicability considerably since in most industrial lines, reach ability differs over the stations to further line reach ability and flexibility. Therefore, in this work we propose a novel generalized simulation-based method for automatic robot line balancing that allows any robot positioning. It reduces the need for robot coordination significantly by spatially separating the robot weld work loads. This is furthermore achieved at a cost neglectable to line cycle time. The proposed method is furthermore successfully demonstrated on an automotive stud welding line. Moreover, algorithm CPU-times is a mere fraction of corresponding manual optimization times.Copyright

Integrating Assembly Design Sequence Optimization, and Advanced Path Planning

Assembling a product is a delicate process at the borderline between design and manufacturing. Shortening the time between them plays a central role both for quality assurance and fast time to market. In this paper, we describe an automatic tool based on a new method, integrating assembly design, sequence optimization, and advanced rigid body path planning. First, we introduce a greedy algorithm for assembling a product, part by part, based on state-of-the-art path planning. We exploit all the six degrees of freedom of a rigid body to search for collision-free paths, instead of limited motions. Then, we use assembly design in order to limit the search for an optimal assembling sequence and to guarantee geometrical quality among the sequences examined. Disassembly path planning is used here to further cut the state space and to give a quality measure to the sequences. Eventually, we present results for an industrial test case, which has been successfully solved by applying our method.

Automatic collision free path planning in hybrid triangle and point models: a case study

Collision free path planning is a key technology for assembly analysis, robot line optimization, and virtual assessment of industrial maintenance and service. The ability to compute collision free paths relies on the ability to quickly and robustly query the proximity of the planning object to its surroundings. Path planning with triangulated models is a well studied problem, however, hybrid models comprising both points and triangles present new and difficult challenges. Working directly with point clouds is becoming more relevant because it allows one to scan existing industrial installations and path plan with the scan data instead of possibly incorrect planned layouts. In this paper we implement and analyze a new hybrid path planning interface on a case study in robot line manufacturing and demonstrate its feasibility in comparison to an existing CAD model of the work environment and show that triangulating the original point cloud is undesirable for path planning.