WO2013141798A1

WO2013141798A1 - Planning of a workshop procedure

Info

Publication number: WO2013141798A1
Application number: PCT/SE2013/050297
Authority: WO
Inventors: Tony Lindgren; Anna Pernestål
Original assignee: Scania Cv Ab
Priority date: 2012-03-20
Filing date: 2013-03-19
Publication date: 2013-09-26
Also published as: EP2828806A1

Abstract

A planning entity, which schedules the work to be performed on a motor vehicle at a workshop visit, includes: an input interface (110), a processor (120) and an output interface (130). The input interface (110) receives an assignment description (AD) including at least one maintenance instance (MI1, MI2, …, MIn) to be handled at the workshop visit. Then, based on the assignment description (AD), the processor (120) generates a work plan (WP) describing a temporal sequence of work operations to execute during the workshop visit. Each maintenance instance (MI1, MI2, …, MIn) is associated with a set of cost parameters ({C1}, {C2}, …, {Cn}) describing a character and an amount of work to be performed when handling the maintenance instance (MI1, MI2, …, MIn). The processor (120) formulates an optimizing problem based on the maintenance instances (MI1, MI2, …, MIn) included in the assignment description (AD) and the sets of cost parameters ({C1}, {C2}, …, {Cn}) associated thereto; and solve the optimizing problem. Thus, the processor (120) derives the work plan (WP) in such a manner that the time required to complete all work operations in said temporal sequence is minimized. The output interface (130) presents the work plan (WP).

Description

Planning of a Workshop Procedure

TH E BACKG ROU N D OF TH E I NVENTION AN D P RIOR ART

The present invention relates generally to the plan ning of workshop visits for motor vehicles. More particularly the invention relates to a plan ning entity according to the preamble of claim 1 . The invention also relates to a method according to the preamble of claim 6, a computer program accordi ng to clai m 1 1 and a computer prog ram product according to claim 1 2.

Service and mai ntenance of mechanical equipment has been needed as long as such equipment has existed . Moreover, especially for motor vehicles i n commercial use, (e.g . trucks and busses) , it is interesting to minimize the downtime, i.e. when the vehicle cannot be used (for example because it is in a workshop for mai ntenance). Hence, there is a balance between the requi- rement to perform maintenance in order to maxi mize the useful lifespan , and the wish to avoid un necessary workshop visits. Historically, tests and theoretical models have been employed to accomplish relevant maintenance programs for different types of products, such as motor vehicles. Within the vehicle industry, it has been common practice to assign intervals for when mai ntenance shall be performed , and which measu res that shall be taken at each maintenance occasion . Recently, various forms of flexible/adaptive mai ntenance schemes have also been introduced , where the maintenance oc- casions depend on how the vehicle is use. Nonetheless, irrespective of how the workshop visits are scheduled, i n order to minimize the downti me, it is interesting to execute each mai ntenance procedure as efficiently as possible.

US 2006/0041 459 describes a method for total effective cost management i n a complex system (e.g. an ai rcraft), which includes creati ng a maintenance plan for the system. The mai ntenance plan includes at least one task performed during mai ntenance of the system . A plu rality of different maintenance schedules are created for performing the task(s) of the maintenance plan . A to- tal effective cost (TEC) associated with each mai ntenance sche- dule is then determined based upon a cost and an availability associated with the maintenance schedule. The availability is based upon a down time and a mission time associated with the maintenance schedule. Thereafter, a maintenance schedule is selected from the plurality of different maintenance schedules based upon the TEC for each maintenance schedule.

US 2005/0080525 discloses a method for defining the time and scope of maintenance operations for a system (e.g . a vehicle) having a plu rality of maintenance items, each of wh ich should be carried out within an assigned tolerance range. A predefined minimu m maintenance interval between successive mai ntenance operations is also presu med . The timing of a maintenance operation is predictively fixed at at least that tolerance range end point which is the first of the tolerance range end points of main- tenance items relating to maintenance ti mes to follow the time of a preceding maintenance operation while complyi ng with the minimu m maintenance interval. At least those maintenance operations whose tolerance range end points occu r before the predicted subsequent maintenance time are defined as the scope of the immi nent maintenance operation. The document also reveals a strategy for planning the working steps to perform in con nection with a particular workshop visit. Here, maintenance items are assig ned maintenance-related parameters, such as the working time required for implementation and the worki ng value associated thereto. A residual run ning time parameter indicates how long it is expected to remain possible to wait for the execution of the mai ntenance item i n question . A cost fu nction is used for an optimization process, seeking to minimize an overall maintenance cost i n terms of money or invoice amount. P ROBLEMS ASSOC IATE D WITH TH E PRIOR ART

Hence, solutions are known for improving the maintenance procedures performed on for example motor vehicles. However, there is yet no process for optimizi ng the work plan for a given maintenance workshop visit in terms of the time required to complete the maintenance work. SUMMARY OF TH E I NVENTION

The object of the present invention is therefore to provide a solution, which enables efficient planning of a motor vehicle's workshop visit, thus reducing the downtime for the vehicle. According to one aspect of the invention , the object is achieved by the initially described maintenance entity, wherein each maintenance instance is associated with a set of cost parameters describing a character and an amount of work to be performed when handling the maintenance instance. The proposed pro- cessor is configured to formulate an optimizing problem based on the maintenance instances included i n the assig nment description and the sets of cost parameters associated thereto. The processor is further configured to solve the optimizing problem, thus deriving the work plan in such a manner that the time requi- red to complete all work operations in the temporal sequence is mini mized.

This planning entity is advantageous because it provides a work plan according to which the maintenance of a motor vehicle can be performed in a hig hly efficient man ner. According to one embodiment of this aspect of the invention, the set of cost parameters associated to each maintenance instance specifies : a deg ree of disassembly of the motor vehicle, a positioning of a technician relative to the motor vehicle, a set of tools required and/or an estimated amou nt of time. Thereby, the key aspects determining the amount of time needed to carry out the maintenance procedure can be modeled.

According to another embodiment of this aspect of the invention, wherein the degree of disassembly of the motor vehicle expresses a set of preceding work operations needed to be executed before it is possible execute a first work operation for handling the maintenance instance as such. This cost parameter is advantageous to consider because thereby the opti mizi ng problem can be formulated very accu rately. Preferably, the degree of disassembly of the motor vehicle is further associated with a ti me parameter indicati ng an estimated amou nt of time required to reach the degree of disassembly from a state wherein the motor vehicle is fully assembled .

According to still another embodiment of this aspect of the invention, the processor is to apply a best-first search algorithm in order to solve the optimizing problem. Namely, such an informed search algorith m (e.g . an A^* algorith m) is efficient because it fi rst searches all routes that appear to be most likely to lead towards the goal for the optimizi ng , i .e. minimal ti me.

According to another aspect of the invention , the object is achie- ved by the method described initially, wherein each maintenance instance is associated with a set of cost parameters describing a character and an amount of work to be performed when handling the maintenance instance. The method fu rther involves formulati ng an optimizing problem based on the maintenance instances included in the assign ment description and the sets of cost parameters associated thereto, and thereafter solvi ng the optimizi ng problem. Thus, the work plan is derived in such a manner that the ti me required to complete all work operations i n a temporal sequence is minimized . The advantages of this method, as well as the preferred embodiments thereof, are apparent from the discussion hereinabove with reference to the proposed planning entity.

According to a further aspect of the invention the object is achieved by a computer prog ram loadable into the internal me- mory of a computer, comprising software for controlling the above proposed method when said program is run on a computer.

According to another aspect of the invention the object is achieved by a computer prog ram product, having a prog ram recorded thereon, where the prog ram is to make a computer control the above proposed method .

BRI E F D ESC RI PTION OF TH E D RAWINGS

The present invention is now to be explained more closely by means of embodiments, which are disclosed as examples, and with reference to the attached drawings. Figure 1 shows a block diagram over a planning entity according to one embodiment of the invention,

Figure 2 illustrates how different sets of cost parameters may be associated to maintenance instances according to one embodiment of the invention, and

Figure 3 shows a flow diagram illustrating the general method according to the invention.

DESCRIPTION OF EMBODIMENTS OF THE INVENTION

We refer initially to Figure 1 showing a block diagram over a pro- posed planning entity for scheduling a motor vehicle's maintenance visit to a workshop. The planning entity includes an input interface 110, a processor 120 and an output interface 130.

The input interface 110 is configured to receive an assignment description AD including at least one maintenance instance MM, MI2, Mln to be handled at the workshop visit. Here, a maintenance instance corresponds a particular measure to be taken, for instance changing an oil filter, changing the engine oil, replacing brake linings or replacing a brake disk.

Each maintenance instance MM, MI2, Mln is associated with a set of cost parameters {C1}, {C2}, {Cn} describing a character and an amount of work to be performed when handling the maintenance instance MM, MI2, Mln. For example, the set of cost parameters, say {C1}, associated to a given maintenance instance MM specifies: a degree of disassembly of the motor vehicle, a positioning of a technician relative to the motor vehicle, a set of tools required and/or an estimated amount of time needed to complete the measures to be taken.

Preferably, the sets of cost parameters {C1}, {C2}, {Cn} are stored in a data storage 140 accessible by the processor 120. Figure 2 illustrates how different sets of cost parameters {C1}, {C2}, {Cn} may be associated to the maintenance instances MM, MI2, Mln according to one embodiment of the invention.

In the example illustrated in Figure 2, a first maintenance ins- tance MM is associated with a first set of cost parameters C1: C , c₁₂, c_1x; a second maintenance instance MI2 is associated with a second set of cost parameters C2: c₂₁, c₂2, c_2y; and an n-th maintenance instance Mln is associated with an n-th set of cost parameters Cn: c_n1, c_n2, c_nz.

Based on the assignment description AD, the processor 120 is configured to generate a work plan WP describing a temporal sequence of work operations to execute during the workshop visit. Specifically, the processor 120 is configured to formulate an optimizing problem based on the maintenance instances MM, MI2, Mln included in the assignment description AD and the sets of cost parameters {C1}, {C2}, {Cn} associated thereto. The processor 120 is further configured to solve the optimizing problem, and thus derive the work plan WP in such a manner that the time required to complete all work operations in said temporal sequence is minimized.

The output interface 130 is configured to present the work plan WP on a human-comprehensible format, e.g. via a computer display. However, alternative/complementary formats are likewise conceivable, such as in the form of a document (electronic and/ or in the form of a print-out) and/or as an e-mail.

According to one embodiment of the invention, the degree of disassembly of the motor vehicle expresses a set of preceding work operations needed to be executed before it is possible execute a first work operation for handling the maintenance instance MM, MI2, Mln as such. Thus, by identifying two or more maintenance instances MM, MI2, Mln involving the same, or similar, degree of disassembly, these maintenance instances may be co-located in time, and the required overall time can be economized. The degree of disassembly of the motor vehicle is preferably also associated with a time parameter indicating an estimated amount of time required to reach this degree of disassembly from a state wherein the motor vehicle is fully assembled. Thereby, any saving of time can be uncovered in a relatively uncomplicated manner by the optimizing algorithm.

The processor 120 is preferably configured to apply a best-first search algorith m in order to solve the optimizing problem. Such an informed search algorithm is advantageous because it first searches the routes that appear to be most likely to lead towards the goal. Here, the A^* search algorith m constitutes one suitable alternative. I n contrast to a greedy best-first search algorithm, the A^* search algorith m does not simply consider the local cost from the previously expanded node, however it also takes the distance already traveled into accou nt, i .e. the historic cost. According to the invention , however, the algorith m applied by the processor 1 20 to solve the optimizing problem may equally well be for example the Dijkstra algorith m or the A2 algorithm.

A g reedy optimizi ng algorithm, on the other hand, is an algorith m that follows the problem solving heu ristic of maki ng the lo- cally optimal choice at each stage with the hope of finding a global optimum. Thus, on some problems, a g reedy strategy does not necessarily produce an optimal solution. Nonetheless, a greedy heu ristic may yield locally opti mal solutions that approximate a global opti mal solution. The above procedu re implemented by the processor 1 20 is preferably controlled by a computer prog ram loaded into a memory 1 60 of the processor 1 20, or an external memory unit accessible by the processor 1 20 (not shown) . The computer prog ram, in tu rn, contains software for controlling the steps of the procedu re when the prog ram is ru n on the processor 1 20.

In order to sum up, the general method of scheduling the work to be performed on a motor vehicle at a workshop visit according to the invention will be described below with reference to the flow diag ram i n figure 3. In a first step 31 0, it is checked whether an assig nment description has been received ; and if so, a step 320 follows. Otherwise, the procedure loops back and stays i n step 31 0.

In step 320, an optimizing problem is formulated based on the maintenance instances included in the assig nment description and the sets of cost parameters associated thereto. Subsequently, in a step 330, the optimizing problem is solved . As a result, the work plan is derived in such a manner that the time required to complete all work operations in said temporal sequen- ce is mini mized. Thereafter, in a step 340, the work plan is presented, for instance via a display, in the form of a docu ment (electronic and/or in the form of a print-out) and/or as an e-mail to one or more predefined recipients. Then , the procedure ends.

The process steps, as well as any sub-sequence of steps, descri- bed with reference to the figure 3 above may be controlled by means of a programmed computer apparatus. Moreover, although the embodiments of the invention described above with reference to the drawings comprise computer apparatus and processes performed in computer apparatus, the invention thus also extends to computer programs, particularly computer programs on or in a carrier, adapted for putting the invention into practice. The program may be in the form of source code ; object code, a code intermediate source and object code such as in partially compiled form, or in any other form suitable for use in the implementation of the process according to the invention. The carrier may be any entity or device capable of carrying the program. For example, the carrier may comprise a storage medium, such as a Flash memory, a ROM (Read Only Memory), for example a CD (Compact Disc) or a semiconductor ROM, an EPROM (Erasable Programmable Read-Only Memory), an EEPROM (Electrically Erasable Programmable Read-Only Memory), or a magnetic recording medium, for example a floppy disc or hard disc. Further, the carrier may be a transmissible carrier such as an electrical or optical signal, which may be conveyed via electrical or optical cable or by radio or by other means. When the program is embodied in a signal, which may be conveyed , directly by a cable or other device or means, the carrier may be constituted by such cable or device or means. Alternatively, the carrier may be an integrated circuit in which the program is embedded, the integrated circuit being adapted for per- forming, or for use in the performance of, the relevant processes.

The invention is not restricted to the described embodiments in the figures, but may be varied freely within the scope of the claims.

Claims

1. A planning entity for scheduling the work to be performed on a motor vehicle at a workshop visit, the planning entity comprising:

an input interface (110) configured to receive an assignment description (AD) including at least one maintenance instance (MM, MI2, Mln) to be handled at the workshop visit, a processor (120) configured to, based on the assignment description (AD), generate a work plan (WP) describing a tem- poral sequence of work operations to execute during the workshop visit, and

an output interface (130) configured to present the work plan (WP), characterized in that

each maintenance instance (MM, MI2, Mln) is associa- ted with a set of cost parameters ({C1}, {C2}, {Cn}) describing a character and an amount of work to be performed when handling the maintenance instance (MM, MI2, Mln), and

the processor (120) is configured to formulate an optimizing problem based on the maintenance instances (MM, MI2, Mln) included in the assignment description (AD) and the sets of cost parameters ({C1}, {C2}, {Cn}) associated thereto, and solve the optimizing problem, thus deriving the work plan (WP) in such a manner that the time required to complete all work operations in said temporal sequence is minimized.

2. The planning entity according to claim 1, wherein the set of cost parameters ({C1}, {C2}, {Cn}) associated to each maintenance instance (MM, MI2, Mln) specifies at least one of: a degree of disassembly of the motor vehicle, a positioning of a technician relative to the motor vehicle, a set of tools required, and an estimated amount of time.

3. The planning entity according to claim 2, wherein the degree of disassembly of the motor vehicle expresses a set of preceding work operations needed to be executed before it is possible execute a first work operation for handling the maintenan- ce instance (MM, MI2, Mln) as such.

4. The planning entity according to any one of claims 2 or 3, wherein the degree of disassembly of the motor vehicle is associated with a time parameter indicating an estimated amount of time required to reach said degree of disassembly from a state wherein the motor vehicle is fully assembled.

5. The planning entity according to any one of the preceding claims, wherein the processor (120) is configured to apply a best-first search algorithm in order to solve the optimizing problem.

6. A method of scheduling the work to be performed on a motor vehicle at a workshop visit, the method comprising:

receiving an assignment description (AD) including at least one maintenance instance (MM, MI2, Mln) to be handled at the workshop visit,

generating, based on the assignment description (AD), a work plan (WP) describing a temporal sequence of work operations to execute during the workshop visit, and

presenting the work plan (WP),

characterized by each maintenance instance (MM, MI2, Mln) being associated with a set of cost parameters ({C1}, {C2}, {Cn}) describing a character and an amount of work to be performed when handling the maintenance instance (MM, MI2, Mln), and the method comprising:

formulating an optimizing problem based on the mainte- nance instances (MM, MI2, Mln) included in the assignment description (AD) and the sets of cost parameters ({C1}, {C2}, {Cn}) associated thereto, and

solving the optimizing problem, thus deriving the work plan (WP) in such a manner that the time required to complete all work operations in said temporal sequence is minimized.

7. The method according to claim 6, wherein the set of cost parameters ({C1}, {C2}, {Cn}) associated to each maintenance instance (MM, MI2, Mln) specifies at least one of: a degree of disassembly of the motor vehicle, a positioning of a technician relative to the motor vehicle, a set of tools required, and an estimated amount of time.

8. The method entity according to claim 7, wherein the degree of disassembly of the motor vehicle expresses a set of preceding work operations needed to execute before it is possible execute a first work operation for handling the maintenance instance (M M , M I2, M l n) as such.

9. The method according to any one of claims 7 or 8, wherein the degree of disassembly of the motor vehicle is associated with a time parameter indicating an esti mated amount of time re- quired to reach said degree of disassembly from a state wherein the motor vehicle is fully assembled.

1 0. The method according to any one of claims 6 to 9, wherein the opti mizi ng problem is solved by applying a best-fi rst search algorithm.

1 1 . A computer prog ram loadable into the internal memory of a computer, comprising software for controlling the steps of any of the claims 6 to 1 0 when said program is run on the computer.

1 2. A computer prog ram product (1 60) , having a prog ram recorded thereon, where the prog ram is to make a computer control the steps of any of the claims 6 to 1 0.